CHAPTER 4 ANALYSIS AND RESULTS

132

4. Analysis and Results .......................................................................... 133

4.1. Profile of the sample surveys .................................................. 133

4.1.1. Opinion survey of tourists ............................................ 133

4.1.2. Survey of attitude of residents ..................................... 134

4.1.3. Survey of accommodation providers ........................... 135

4.2. Life Cycle Analysis .................................................................. 135

4.2.1. Kerala Tourism ............................................................. 136

4.2.2. Kovalam beach ............................................................ 158

4.2.3. Thekkady ...................................................................... 168

4.3. Measurement of factors that influence the life cycle ............... 179

4.2.1. Destination experience................................................. 179

4.2.2. Quality of resources ..................................................... 180

4.2.3. Attitude of residents ..................................................... 184

4.2.4. Natural ambience of the site ........................................ 190

4.2.5. Urbanisation / Disappearing rural characteristics ........ 193

4.2.6. Commercial land use / Private sector investment........ 195

4.2.7. Transition from tourism ................................................ 196

4.2.8. Local participation ........................................................ 199

4.2.9. Occupancy of tourist accommodation .......................... 200

4.2.10.Historicity ...................................................................... 201

4.2.11.Tourism promotion ....................................................... 204

 

133

4. Analysis and Results 

4.1. Profile of the sample surveys

The primary surveys conducted for this research were mainly to construct the

destination experience of the tourists and the attitude of residents of the destinations.

A third survey was to supplement the information available for the accommodation

sector. The salient features of the samples are presented below.

4.1.1. Opinion survey of tourists 

• The sample size was 530 foreign tourists at Kovalam and 295 at Thekkady.

Most of the tourists who were interviewed were from UK, Sweden, Germany,

France, Italy, USA and Canada.

• About one-fifth of the visitors were repeat visitors. 79% of tourists to

Kovalam and 89% of tourists to Thekkady were first-timers.

• The primary reason for the visits to both the destinations was stated as

‘vacation’.

• Mainly friends/relatives, internet searching and tour operators provided the

information about the destinations.

• Goa, Varkala, Kochi, Thailand and Maldives are stated as the competing

destinations to Kovalam. Munnar and Kochi are the competing destinations to

Thekkady.

• The main shopping items of tourists were textiles, ornaments and handicrafts.

• Average duration of tourists at Kovalam was 10.53 days. At Thekkady, the

tourists spent on an average 2.89 days.

134

• Average daily expenditure of a tourist at Kovalam was Rs. 3237. At Thekkady

this was Rs. 2805.

4.1.2. Survey of attitude of residents 

• The sample size of resident households surveyed at Kovalam was 181 and 139

at Thekkady.

• There were 625 persons in the sample households at Kovalam and 561 persons

in the sample surveyed at Thekkady. The average household size was 3.45 at

Kovalam and 4.04 at Thekkady.

• The sex ratio of Kovalam was 806 females for 1000 males. At Thekkady,

there were 1011 females for 1000 males in the sample.

• The worker participation rate at Kovalam was about 40% and the same at

Thekkady was 38%.

• The primary sector engaged 38% of the working force at Kovalam and 43% at

Thekkady. Only very few persons in the sample were engaged in the

secondary sector.

• Over 80% of the sample at Kovalam was confident that tourism would be the

most important industry in the State. Only 61% of the sample at Thekkady

shared this opinion. Kovalam is primarily a tourist destination, whereas,

Thekkady is also a spices trading centre.

• Non-availability of land due to tourism development is a major issue at

Thekkady compared to Kovalam.

135

4.1.3. Survey of accommodation providers 

• There were 76 accommodation establishments in the study area at Kovalam

and 91 at Thekkady. Majority of the establishments at Thekkady, numbering

50, was home stays. Number of establishments which responded was 50 at

Kovalam and 41 at Thekkady (22 hotels and 19 home stays).

• In 2007, the number of tourist beds available in the contacted establishments

was 2087 at Kovalam and 1687 at Thekkady.

• 20 hotels in Kovalam and 36 hotels and home stays in Thekkady provided the

occupancy rates. The occupancy rates of these establishments in the peak

tourist season were 87% and 78% during the year 2007 respectively for

Kovalam and Thekkady.

• The employment details were provided by 13 hotels in Kovalam and 27 hotels

and home stays in Thekkady. The 13 hotels in Kovalam employed 179 persons

and the 27 hotels and home stays in Thekkady employed 506 persons.

The general tables generated from the primary surveys are given in Appendix 4.1.

Analysis of the primary data, as required for meeting the objectives of the research, is

presented at the respective sections of this chapter. The section that follows discusses

the findings of the life cycle analysis. This is followed by measurement of factors that

influence the life cycle of the selected destinations.

4.2. Life Cycle Analysis

As reviewed earlier, the product life cycle concept can describe a product class, a

product form or a brand. The product classes have the longest lifecycle whereas the

life cycle of a specific brand can change quickly because of reasons like competition

136

(Kotler, Bowen, & Makens, 1999). Tourist arrivals to India depend on the world

tourism demand and tourist arrivals to Kerala depend on the tourist arrivals to India.

Demand for product forms in Kerala like beaches or backwaters depend on the tourist

arrivals to Kerala. The demand for each product form influences the tourist arrivals in

specific destinations or brands. In other words, the immediate superset influences the

life cycle of the brand or product form.

Analysis of life cycle hence cannot be taken up independently of the universe it

belongs to. In the present research also, the life cycle analysis of the selected brands –

Kovalam and Thekkady – is preceded by the life cycle analysis of Kerala tourism,

which can be termed as the product class in which the selected brands belong.

4.2.1. Kerala Tourism 

i. Growth of tourism

It was during the 7th five-year plan period that the Government of Kerala took up

tourism promotion activities, realising the potential of tourism development in Kerala

(Department of Tourism, Government of Kerala, 2002). The Government declared

tourism as an industry in 1986 and the industry was greeted with incentives and

concessions for making investments and promoting tourism. Today, the State has

emerged as one of the most acclaimed tourist destinations in the country. International

recognition of Kerala tourism came in various forms. The World Travel and Tourism

Council (WTTC) selected Kerala as a Partner State. ”National Geographic” chose

Kerala as “one of the 50 must see destinations of a life time”. “Travel and Leisure”

describes Kerala as one of the 100 great trips for the 21st Century. “Cosmopolitan”

137

rates Kerala as one of the ten love nests in India. “Khaleej Times” sees Kerala as one

of the six destinations of the millennium.

A study by Tata Consultancy Services carried out a situation analysis of Kerala

tourism and presented it in the form of a SWOT analysis (TCS, 2000). Though the

study was conducted in the year 2000, the strengths identified in the study give an

indication of the reasons for the commendable growth that Kerala tourism has

achieved. The strengths identified in the study are reproduced below:

• Excellent nature resources in the forms of backwaters, hill-stations and

beaches

• Kerala is the seat of Ayurveda, a very important constituent of the growing

body-mind/ alternative medicine

• Temperate climate throughout the year

• A very good reputation both internationally and nationally

• High compounded annual growth rate of 12% for tourists

• High level of literacy among residents enabling better interface with tourists

• It has both tourist destinations and tourism assets that commute to

destinations. This offers tourists an opportunity to spend their entire stay on a

tourism resource

A remarkable feature of the growth of foreign tourists to Kerala is its emergence as an

important destination in India, in spite of its location far and outside the traditional

Golden Triangle connecting Delhi, Agra and Jaipur. About ten percent of the foreign

tourists, coming to India visit Kerala. In the case of domestic tourists, the trend is

showing a consistent growth, though not impressive as that of foreign tourist arrivals.

But on the other side, the achievement in the growth is to be viewed taking into

account the geographic location of Kerala far away from the tourist origins in the

country and further discouraged by the pricing of the transport connections.

138

Kerala Tourism is subjected to studies by different agencies besides the Tourism

Department of Kerala. The number of tourist arrivals in Kerala has already

outnumbered the projected figures given for the year 2010. Kerala Tourism Vision

2025 projected the foreign tourist arrivals at 4.32 lakhs, World Tourism Organization

(UNWTO) estimated the figure as 5.1 lakhs and the World Tourism and Travel

Council (WTTC) put the figure at 5.06 lakhs, all for the year 2010. The actual tourist

arrivals have crossed these estimates in 2007.

Number of foreign tourist arrivals to the State was 51816 in 1987. In seven years, this

was doubled. It took just another six years to double again and reached the figure of

209933 in 2000. In 2006, the number of tourist arrivals was 428534 and crossed the

five lakh mark in 2007. The tourist arrivals from 1987 to 2007 are given in Table 4.1.

ii. Seasonal Characteristics

Seasonal variation in tourist arrivals is a phenomenon experienced by most of the

tourist destinations in India. Kerala tourism considers the six months from October to

March as the tourist season, and most of the foreign tourist arrivals are in this period.

Challenging this seasonality is always seen as an important strategy for economic

rewards by the tourism industry. By looking at the nationality of foreign tourists

coming to Kerala, the majority is from Europe and the winter season in the countries

in the region coincides with the tourism season of Kerala.

Monthly tourist arrivals from 1988 to 2006 are used to compute seasonal indices.

Pattern of seasonal indices over the years is changing (Table 4.2). The most ideal

situation is when the indices remain the same with the value 100 all through a year.

139

The seasonal index was always the highest in the month of January as far as Kerala

tourism is concerned. Similarly, June was the leanest month for tourist arrivals.

Quarterly trend in the values of the seasonal indices are presented in Figure 4.1. A

reduction in higher index values in the peak season and an increase in lower index

values in lean season in a growing tourism market would indicate a trend that would

point to the ideal situation referred earlier. The first and fourth quarters of the year

constitute the tourist season and the middle two quarters are lean seasons. In the first

quarter, index values of February and March are on the rise. All the other four months

in the peak season are witnessing a decreasing trend in the index values. The tourist

arrivals in all the three months in the second quarter, July and August in the third

quarter contribute to an increasing trend in the index values.

The change in the pattern of tourist arrivals over the months in a year is turning out as

an outcome that could improve the economic sustainability of tourism industry. This

could lead to higher occupancy of tourist accommodation in the second and third

quarter, more stable employment opportunities, and better management of tourism

destinations. Though in terms of index values there is a change slowly emerging in

the pattern, in absolute terms, the growth of tourism is still contributed by the increase

in tourist arrivals in the peak season. The increase in tourist arrivals for the periods

from 1990 to 1995, 1995 to 2000 and from 2000 to 2005 is in Table 4.3. Considering

the fact that the investments made in tourist accommodation that increased the

number of beds in the last ten years, the tourist arrivals are at par or below the

capacity levels even in the peak season. The spread of tourist arrivals over the months

could be perhaps the most important contributing factor for the future growth of

tourism in the State.

140

Table 4.1: Monthly tourist arrivals in Kerala for the years from 1987 to 2007 Month 1987 1988 1989 1990 1991 1992 1993January 7881 7781 9696 9139 9341 11037 10819February 5797 5745 7713 7625 7287 9472 9667March 4365 3970 5905 6111 5904 6975 8199April 3325 2157 3257 3719 4243 6097 6696May 1583 1194 1798 3232 3124 4911 5229June 1091 857 1401 2502 2532 4873 4814July 1343 1734 2683 3244 3729 4304 5760August 3111 3244 3849 4476 4338 7062 7627September 4391 2132 3200 4286 4906 6829 7189October 5409 6542 6320 6384 6220 8582 8326November 6602 8072 8209 6814 7701 9948 9443December 6918 8655 8921 8607 9984 10545 11440Total 51816 52083 62952 66139 69309 90635 95209Month 1994 1995 1996 1997 1998 1999 2000January 13544 20313 21859 24773 28108 31541 24388February 10941 17942 20294 20354 23656 25624 23268March 8232 15938 20149 19134 20546 20816 17499April 5847 9019 11467 11852 16493 14277 13964May 4341 6183 6758 8751 11355 10398 12923June 4875 3894 5490 7643 5755 8040 8306July 4383 7331 8019 10147 5535 10656 8514August 5030 11662 12751 11896 10024 14487 17764September 16598 11524 13767 10003 12385 11806 18222October 16346 11061 12185 11917 12531 13367 17344November 5662 13431 20422 19542 19208 19007 22592December 8769 14674 23694 26415 25994 22154 25149Total 104568 142972 176855 182427 191590 202173 209933Month 2001 2002 2003 2004 2005 2006 2007January 31625 29440 41845 45630 43345 58858 72814February 30862 29105 36163 43418 41314 56530 66131March 21957 19246 25261 35006 33479 39584 56151April 17868 18028 20106 23546 20191 32377 34487May 10653 10794 12675 14870 14919 20470 21098June 6571 6610 10820 12734 13239 16209 18262July 7747 8581 14824 17228 17593 23578 25199August 13611 14226 19240 27341 24398 28821 35563September 12391 17808 20253 21103 20064 21888 24708October 11913 20744 24702 22160 28068 28681 33534November 19310 26190 32165 38118 42324 44421 55647December 24322 31792 36567 44392 47565 57117 72214Total 208830 232564 294621 345546 346499 428534 515808Source: Tourist Statistics (various years), Department of Tourism, Government of Kerala

141

Table 4.2: Seasonal Indices for tourist arrivals in Kerala Month 1988 1989 1990 1991 1992 1993 January 196 191 167 173 160 141 February 144 150 138 135 134 124 March 102 113 109 109 96 105 April 56 62 66 78 82 86 May 30 34 58 57 64 67 June 21 27 45 45 63 62 July 41 51 59 66 55 72 August 74 74 81 74 91 94 September 47 61 78 82 87 88 October 140 120 116 102 109 102 November 170 154 124 123 125 117 December 181 164 157 156 133 142 Month 1994 1995 1996 1997 1998 1999 2000 January 179 184 161 166 176 186 154 February 147 157 148 136 151 148 147 March 107 138 146 129 131 119 108 April 70 81 82 81 104 82 84 May 51 55 47 60 72 59 76 June 59 33 37 52 36 46 48 July 52 61 52 68 35 63 48 August 56 95 81 78 62 88 97 September 174 92 88 65 76 73 97 October 164 86 78 76 77 83 91 November 56 104 130 123 120 117 118 December 86 113 149 166 161 136 132

Month 2001 2002 2003 2004 2005 2006 January 170 173 186 164 161 176 February 167 170 158 153 154 167 March 122 111 109 122 126 116 April 102 101 86 82 75 95 May 62 58 53 52 55 60 June 39 34 44 43 48 47 July 46 43 60 58 62 66 August 81 68 76 93 83 79 September 75 83 78 72 66 58 October 72 95 93 76 90 74 November 117 120 121 132 133 115 December 147 143 136 153 148 147

142

Table 4.3: Monthly variation in tourist arrivals 1990 to 1995 1995 to 2000 2000 to 2005

January 2.22 times 1.20 times 1.78 times February 2.35 “ 1.30 “ 1.78 “ March 2.61 “ 1.10 “ 1.91 “ April 2.43 “ 1.55 “ 1.45 “ May 1.91 “ 2.09 “ 1.15 “ June 1.56 “ 2.13 “ 1.59 “ July 2.26 “ 1.16 “ 2.07 “ August 2.61 “ 1.52 “ 1.37 “ September 2.69 “ 1.58 “ 1.10 “ October 1.73 “ 1.57 “ 1.62 “ November 1.97 “ 1.68 “ 1.87 “ December 1.70 “ 1.71 “ 1.89 “

iii. Tourist projections

With the capacity level still high, Kerala is expected to maintain higher growth in

tourist arrivals. The time series data from 1988 to 2006 is used to fit a model with the

objective of projecting the tourist arrivals for the coming years. Using a 12-month

moving average, the actual arrivals are de-seasonalized before attempting for

projections. The best fit obtained is a 4th degree polynomial and the estimated model

is as follows:

Y = 5174.3373 – 99.1046 x + 3.8887 x2 – 0.0283 x3 + 7.0108 e-005 x4

(Standard error = 1356.006, Correlation coefficient = 0.9886), where, Y is the number

of foreign tourist arrivals and x is the time variable. Value of x is the serial number of

months in a year with the value 1 for January 1988. The scatter plot and the estimated

polygon are shown in Figure 4.2. The seasonal indices for the months are applied on

the de-seasonalized projection figures obtained from the model and the tourist arrivals

for the three years from 2008 are estimated as given in Table 4.4.

143

Table 4.4: Estimated tourist arrivals to Kerala Month\ Year 2008 2009 2010 January 83639 102006 125108 February 80661 98435 120764 March 56948 69539 85337 April 47408 57922 71098 May 30437 37207 45682 June 24238 29645 36404 July 34604 42344 52007 August 42113 51555 63331 September 31437 38502 47302 October 40784 49969 61399 November 64451 78995 97070 December 83777 102719 126233 Total 620497 758838 931735 Growth rate 20.30 22.30 22.78

Globally, the increase in international tourist arrivals is projected to be around 3 to

4% for the year 2008 and anticipates a long-term growth rate of 4.1% a year through

2020 (UNWTO, 2008). Region-wise forecasts for international tourist arrivals are as

given below:

2007 Forecast 2008 World 6.1% 3 to 4% Europe 4.2% 3 to 4% Asia and the Pacific 10.2% 8 to 10% Americas 4.7% 1 to 3% Africa 7.9% 6 to 8% Middle east 13.4% 6 to 10% Source: UNWTO World Tourism Barometer, Volume 6, No.1, January 2008

In 2001, the share of tourist arrivals in India was 0.37% which increased every year

and reached 0.55% in 2007. Tourist arrivals to India were growing at impressive rates

since 2003. The arrivals increased by 26.8% from 2003 to 2004, by 13.3 % from 2004

to 2005, by 13.5% from 2005 to 2006 and by 11.9% from 2006 to 2007 (Ministry of

Tourism, Government of India, 2008). If the world tourist arrivals maintain the same

144

rate of growth of 6%, and if the share of tourist arrivals maintain the share of 0.55%

recorded in 2007, and if the share of Kerala tourism is maintained at the same rate as

in 2007, the projected foreign tourist arrivals would be as given below:

2008 2009 2010 World tourism 952 million 1009 million 1070 million India tourism arrivals 5.6 million 6.2 million 7 million Kerala tourism 0.58 million 0.65 million 0.73 million

The above estimates assume maintaining of the present trend and ignore the growth

potential. The projected tourist arrivals to Kerala given in Table 4.4 are higher than the

estimates given above. Though the international tourist arrivals are slowing down, the

decline is minimum in the Asia and Pacific region. The market share of American

tourists in Kerala is below 15% and the economic recession, which is highlighted as

the reason for the decreased rate of growth, is not likely to make a great impact on

Kerala tourism. Like the Olympics held at China in 2008, India is hosting the

Commonwealth games in 2010. The game is capable of pulling more European

tourists to Kerala since tourists from UK form the biggest group nationality-wise.

145

Figure 4.1: Pattern of changes in seasonal indices with respect to foreign tourist arrival in K

erala

146

iv. Identification of life cycle stage

The shape of the curve and the projected figures for the years up to 2010 indicate that

Kerala tourism is on its growth path. The real take off seems to have taken place in

the year end of 2001. The beginning of the ‘introduction’ stage is before 1987 and not

included in the above analysis.

Characteristics of sales, cost, profit, customers, market and competition show

differently in the life cycle stages of a product as presented in the Review of literature.

These characteristics are discussed below with respect to Kerala tourism.

Sales: There will be low sales in the ‘Introduction’ stage and this will be rapidly rising

in the ‘Growth’ stage (Kotler, Keller, Koshy, & Jha, 2007). Sales will be peak in the

‘Maturity’ stage and will decline in the ‘Decline’ stage. In the case of tourism, sales

S = 1356.00599216r = 0.98858774

Year 1988 to Year 2006

Num

ber o

f tou

rists

0 42 84 125 167 209 251352

7352

14353

21354

28354

35355

42355

Figure 4.2: The scatter plot of de-seasonalised tourist arrivals and the polynomial curve showing the foreign tourist arrival pattern in Kerala

147

could be represented by the foreign exchange revenue or the number of tourist

arrivals. In the present analysis, sale is represented by the number of tourist arrivals.

Tourist arrivals are maintaining double digit growth rate for the years since 2002,

except for 2005, as can be seen below. Low growth was recorded for the ten years

between 1988 and 2001, revealing the characteristics of the ‘introduction’ stage of the

life cycle.

Year Growth rate (%)

1988 0.521989 20.871990 5.061991 4.791992 30.771993 5.051994 9.831995 36.731996 23.71997 3.151998 5.021999 5.522000 3.842001 -0.532002 11.372003 26.682004 17.282005 0.282006 23.682007 20.37

Costs per tourist: The costs to be considered include the operating costs and overhead

costs in a typical commercial establishment. In the context here, the relevance is more

for the cost incurred by the Government, since Kerala tourism is taken as a product

and the management of the product is by the Government. Expenses of tourism by

Government fall into two broad heads – plan expenditure and non plan expenditure.

Non-plan expenditure is for meeting the establishment costs of Department of

148

Tourism and can be considered as operation expenses. Plan expenditure includes

capital expenditure. For budgeting convenience, investment in infrastructure, which is

of capital investment in nature, is included under revenue expense. For analysis

purpose, this is separated. Most of these investments are in long term assets like

buildings, roads, and other civil construction works. Economic life of these assets is

longer. Kerala Tourism Development Corporation (KTDC), the Government owned

company, accounts 5 to 10% value of such assets in its annual financial statements.

Assuming the same, 10% of the investment in infrastructure and capital is added to

the non-plan expenses to reflect the cost of such investments from the subsequent year

onwards.

The expenses are compiled for the years from 1992-93 to 2006-07 from the

Administrative Reports of Department of Tourism, Government of Kerala. These are

converted to constant prices using Consumer Price Index with base year 1982 as 100.

The number of foreign and domestic tourist arrivals is recalculated for the financial

year periods from April to March. Costs per tourist computed thus are presented in

Table 4.5. As per the pattern, the operating expenses have come down and more or less

stabilized since 2000. Per customer cost is usually high in the introductory stage of a

product life cycle, but comes down in the growth stage and will be lowest in the later

stages. In the case of Kerala tourism also, the operating cost shows a declining trend

as can be seen in Figure 4.3: Pattern of changes in expenditure per tourist. Though it

is difficult to identify the life cycle stage from the figures and graph, the pattern

clearly is moving towards the growth stage of the life cycle.

149

Table 4.5: Index values showing changes in pattern of expenses per tourist Operating expense Capital expense

1992-93 100 100 1993-94 122 113 1994-95 50 88 1995-96 33 75 1996-97 22 125 1997-98 28 175 1998-99 28 113 1999-00 33 113 2000-01 33 113 2001-02 33 113 2002-03 22 175 2003-04 39 150 2004-05 39 163 2005-06 39 213 2006-07 39 163

Figure 4.3: Pattern of changes in expenditure per tourist

Profits: The general characteristics of the life cycle in terms of profit is that it would

be negative in the introduction stage, but rises in the growth stage and will have the

highest profit level in the maturity stage. In the case of Kerala tourism, the earnings in

0

50

100

150

200

250(Index value for 1992‐93 taken as 100)

Operating expense Capital expense

150

foreign exchange is taken as the variable representing profit. The actual profit

includes the earnings from domestic tourists as well as the cost incurred by the private

sector. Since intention here is only to get a trend in the accrual of profit, the net

foreign exchange earnings in the view point of the government is taken. Foreign

exchange earnings less the government expenditures are given in Table 4.6. The

figures are brought to a common base using the Consumer Price Index with 1982 as

base year. It can be seen that the net earnings were positive from the first year taken

into account for the analysis here. The net earnings is increasing as can be seen in the

Figure 4.4: Net earnings at constant prices, which is characteristic of the growth stage

of a product life cycle.

Table 4.6: Foreign exchange earnings for the years from 1992-93 to 2006-07 (Rupees in crores)

Total earnings* (Current prices)

Net earnings (Current prices)

Net earnings (Constant prices)

1992-93 59.75 55.08 22.95 1993-94 105.72 99.09 38.41 1994-95 116.11 111.39 39.22 1995-96 158.76 151.28 48.33 1996-97 196.38 189.15 55.31 1997-98 273.2 264.44 72.25 1998-99 302.08 290.89 70.26 1999-00 416.07 402.96 94.15 2000-01 525.3 510.63 115.01 2001-02 535 519.18 112.13 2002-03 705.67 693.81 143.94 2003-04 983.37 962.3 192.46 2004-05 1266.77 1245.09 239.44 2005-06 1552.31 1526.66 281.67 2006-07 1988.4 1961.9 338.84

*Source: Tourist Statistics (various years, Department of Tourism, Government of Kerala

151

Figure 4.4: Net earnings at constant prices

Customers: The customers of the product are the tourists. ‘Innovators’ visit the

destination in the ‘introduction’ stage and ‘early adopters’ in the growth stage (Kotler,

Keller, Koshy, & Jha, 2007). Lack of information does not permit classification of

tourists into ‘innovators’ and ‘early adopters’. However, studies conducted in earlier

occasions have categorized the tourists based on the frequency of visits to Kerala.

According to a survey conducted on behalf of Department of Tourism in 2006, 58.5%

of the foreign tourists were visiting Kerala for the first time and 29.9% visited Kerala

twice (Department of Tourism, Government of Kerala, 2007). Thus the first timers are

dominating the share which can be taken as an indication of the introduction or

growth stages. Higher share of repeat visitors is an indication of the maturity stage of

a destination. According to another study, majority of the international visitors to

Kerala fall in the age group 21 – 35 years (TRKL, 2001).

Market: Most of the tourists to Kerala were from Europe in all these years. In the

second place was Asia and Pacific. Except from Sri Lanka, tourist arrivals from all

0

50

100

150

200

250

300

350

400

Rupe

es in

 Crores

(Base year 1982)

152

other countries in this market were increasing. USA is the other prominent market for

Kerala tourism. The share of markets is given in Table 4.7. As shown in Figure 4.5, the

indices of growth in tourist arrivals from all these markets were on the rise. It cannot

be said that the markets have shown signs of consolidation and the trend seen is

growth. As per the Butler’s (1980) model, characteristics of the market are more

comparable with the development stage of life cycle.

Table 4.7: Market share of world tourism markets in Kerala tourism

Year Europe Asia and Pacific Americas Africa

Middle East Total

1995 63 23 10 1 4 100 1996 55 32 11 0 2 100 1997 56 30 12 0 3 100 1998 57 29 11 0 3 100 1999 58 29 10 0 4 100 2000 52 30 14 1 4 100 2001 58 25 13 1 3 100 2002 55 24 16 1 4 100 2003 58 21 12 1 8 100 2004 60 21 12 1 6 100 2005 57 23 12 2 7 100 2006 58 20 13 2 7 100

Figure 4.5: Indices of growth in tourist arrivals from world tourism markets

0

100

200

300

400

500

600

700

800

900

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

Europe Asia and Pacific Americas Africa Middle East

153

Competitors: Kerala figures in the top 10 States in India that attracts maximum

number of foreign tourists. The share of Kerala and the other nine states are given in

Table 4.8. Among the ten states, Andhra Pradesh, Karnataka, West Bengal, Delhi and

Rajasthan have managed to show an increasing trend in the market share from 2001 to

2006. Though marginal, Kerala is among the other five states that experienced a

declining trend in the market share. The upward and downward trends can be seen in

Figure 4.6 and Figure 4.7. Two states in south India – Karnataka and Andhra Pradesh

are the competing States in South India which have made a dent in the market share of

Kerala. At the same time, Rajasthan continues to be the State that attracts maximum

number of foreign tourists and the State has strengthened its position between 2001

and 2007. Goa is Kerala’s primary competitor as per a study and 15% of international

visitors and 11% of domestic visitors consider Goa as an alternative destination

(TRKL, 2001). But in the number of foreign tourist arrivals, Goa ranks below Kerala.

154

Table 4.8: Top 10 States in India with maximum foreign tourist arrivals Percentage of foreign tourist arrivals

2001 2002 2003 2004 2005 2006 20071. Andhra Pradesh

State arrivals to gross state arrivals 1.24 4.08 7.14 5.99 5.63 5.7 5.85State arrivals to country arrivals 2.65 8.82 17.58 14.49 14.29 15.06 15.15

2. Goa State arrivals to gross state arrivals 4.78 5.27 4.68 4.34 3.39 3.24 3.02State arrivals to country arrivals 10.25 11.39 11.53 10.51 8.59 8.55 7.82

3. Karnataka State arrivals to gross state arrivals 2.59 1.15 3.72 6.34 5.48 4.3 4.06State arrivals to country arrivals 5.55 2.5 9.17 15.34 13.91 11.37 10.52

4. Kerala State arrivals to gross state arrivals 3.84 4.51 4.39 4.13 3.48 3.65 3.92State arrivals to country arrivals 8.23 9.75 10.81 9.99 8.84 9.64 10.15

5. Maharashtra State arrivals to gross state arrivals 16.84 14.91 14.69 14.57 14.57 14.57 14.58State arrivals to country arrivals 36.08 32.25 36.19 35.24 37 38.5 37.77

6. Rajasthan State arrivals to gross state arrivals 11.19 8.31 9.36 11.62 11.37 10.39 10.64State arrivals to country arrivals 23.97 17.97 23.06 28.11 28.87 27.44 27.57

7. Tamil Nadu State arrivals to gross state arrivals 14.22 15.6 13.42 12.66 11.85 11.23 12.93State arrivals to country arrivals 30.47 33.75 33.07 30.6 30.1 29.67 33.52

8. Uttar Pradesh State arrivals to gross state arrivals 14.62 13.77 12.28 12.41 11.81 11.31 11.34State arrivals to country arrivals 31.33 29.78 30.26 30 29.97 29.88 29.38

9. West Bengal State arrivals to gross state arrivals 5.23 10.26 10.5 9.28 9 8.5 8.77State arrivals to country arrivals 11.2 22.2 25.88 22.44 22.86 22.44 22.72

10. Delhi State arrivals to gross state arrivals 15.27 10.53 10.33 10.04 15.2 16.81 15.33State arrivals to country arrivals 32.72 22.77 25.45 24.28 38.58 44.41 39.73

155

In the Butler’s (1980) model, the ‘introduction’ and ‘growth’ stages are represented

by the four stages – exploration, involvement, development and consolidation.

Number of visitors is limited during the exploration stage, but increases as the life

cycle moves to involvement, development and consolidation stages. Formation of

Department of Tourism and recognition of tourism as an industry are indicators of the

Figure 4.6: States that have managed to increase the market share

Figure 4.7: States that experience a decrease in the market share

156

involvement of Government and the people in developing tourism in Kerala.

Investments happen in the developing stage. From the part of the Government,

investment in infrastructure projects is showing an increasing trend. Most of the

private sector investment in a tourism destination is for developing tourist

accommodation. The number of beds made available to tourists for the years from

1992-93 to 2006-07 are also given in Table 4.9. There will be intensive marketing

efforts in the developing stage as per the Butler’s model. The marketing expense of

the Government calculated on per-foreign-tourist basis is also shown in Table 4.9. As

per the three indicators given in Table 4.9, the life cycle of Kerala tourism falls in the

development / consolidation stage.

As identified by Cooper and Jackson (1989), there is no single measure that could be

used to identify the current stage of life cycle of a product. However, the

characteristics examined above, help to identify the current stage of life cycle of

Kerala tourism as the Growth stage. In terms of the stages identified by Butler (1980),

Kerala Tourism is in the development stage as can also be seen in Table 4.10, using the

indicators identified by Getz (1990) in the case of Niagara Falls:

157

Table 4.9: Investment in infrastructure

Year

Infrastructure investment by Government (Rupees

per foreign tourist at Constant prices)

Number of tourist beds

Marketing expense by Government (Rupees per foreign tourist at Constant

prices) 1992-93 22.78 35.81 1993-94 27.42 4208 39.21 1994-95 50.62 47.49 1995-96 91.00 42.25 1996-97 83.55 40.88 1997-98 92.01 51.71 1998-99 87.95 38.57 1999-00 99.31 7162 55.55 2000-01 93.71 8440 55.69 2001-02 104.08 9279 74.78 2002-03 320.23 10875 80.4 2003-04 204.33 9804 76.09 2004-05 234.27 13275 67.95 2005-06 253.97 15497 69.31 2006-07 222.56 16148 40.54

Table 4.10: Matching of indicators in the development stage Sl No.

Indicator Reflection on Kerala tourism currently

Growth stage that matches the situation

1 Rapid growth in visits Growth of tourist arrivals is high Growth 2 Visitors outnumber

residents Getz (1990) included this as an indicator for a destination. In the case of Kerala tourism, even at the most popular destinations in the state, visitors do not outnumber residents.

Growth

3 Well-defined market area As it stands today, a well defined market has emerged with Europe in the lead. But the market share of Europe is being replaced by other markets

Growth

4 Heavy advertising Marketing by Government forms 10 to 15% of the budgeted expenditure.

Growth

5 External investment leads to loss of local control

Because of the laws and regulations, investors are controlled by Government.

No conclusion

158

4.2.2. Kovalam beach 

i. Growth of tourism

Till the seventies, Kovalam was just a fishing village and a hippy idyll (Lonely Planet,

2000). The beautiful beach line at Kovalam in the shape of four crescents got the

attention of visitors in the 1930s. The Vizhinjam Light House and the Kovalam

Palace were the only monumental buildings in Kovalam (Committee on Scientific

Study of Kovalam, 2002). It was in 1966 that Government of India took the initiative

to develop Kovalam as a major beach resort in South India. Private entrepreneurs also

have started showing interest in developing Kovalam along with ITDC. And today,

Kovalam is one of the most sought after destinations for tourists who visit Kerala.

Till the end of the eighties, nearly two-thirds of the foreign tourists who visited Kerala

were attracted to Kovalam. There were ups and downs in the tourism demand at

Kovalam since then. By the turn of this century, the share of Kovalam declined to

about one-sixth and it showed some improvement in 2006 and 2007, and as per the

latest figures available, the share of Kovalam stands above 20%. The monthly tourist

arrivals for the years from 1988 to 2007 are given in Table 4.11. In 2007, the number

of tourist arrivals at Kovalam crossed the one lakh mark.

ii. Seasonal characteristics

January was the month with the maximum tourist arrivals for most of the years and

the lean months were June and July. The seasonal indices however showed

fluctuations over the years and cannot be treated as following constant indices. The

seasonal indices for Kovalam for the months from 1988 to 2006 are given in Table

4.12.

159

Quarterly trend in the values of seasonal indices are presented in Figure 4.8.December

in the fourth quarter and all the six months in the first and second quarters show an

upward trend in the values of seasonal indices. The peak months in Kovalam are the

five months from November to March. The trend is that the peakness of November is

flattening.

The changes in the seasonal indices mentioned above are results of analysis of a

longer period and by considering the tourist arrivals in all the individual years. This

analysis may not reflect the short term variations that get noticed. Monthly variation

in tourist arrivals at Kovalam is given in Table 4.13. Since 1995, monthly tourist

arrivals have been increasing for the five months from November to February. But

between 2000 and 2005, tourist arrivals in March have increased more than two times.

In contrast with the performance of tourism for the State as a whole, Kovalam has ups

and downs in monthly tourist arrivals from time to time.

160

Table 4.11: Monthly tourist arrivals at Kovalam Month 1988 1989 1990 1991 1992 1993 January 5662 6285 5620 5416 5580 5096 February 4181 5000 4689 4225 4788 4554 March 2889 3828 3758 3423 3526 3862 April 1570 2111 2287 2460 3082 3154 May 869 1166 1988 1811 2483 2463 June 624 908 1539 1468 2463 2268 July 1262 1739 1995 2162 2176 2713 August 2361 2495 2753 2515 3570 3593 September 1551 2074 2636 2845 3452 3387 October 4761 4097 3926 3607 4338 3922 November 5874 5321 4190 4465 5029 4448 December 6298 5783 5293 5789 5331 5389 Total 37902 40807 40674 40186 45818 44849

Month 1994 1995 1996 1997 1998 1999 2000 January 3650 4990 4432 6044 6247 6449 5124 February 2949 4408 3930 5053 5083 5112 5418 March 2219 3915 4824 5206 5165 5123 2589 April 1576 2216 2704 2139 2974 3809 3248 May 1170 1519 660 1539 2508 3477 4156 June 1314 957 432 1215 1936 2656 1798 July 1181 1801 1038 1067 2185 3303 1647 August 1356 2865 2295 1734 2641 3547 3654 September 4474 2831 2305 1587 2338 3089 3649 October 4406 2717 3470 2201 2821 3441 2978 November 1526 3299 5367 5500 5117 4733 4986 December 2363 3605 5817 6099 5640 5180 5193 Total 28184 35123 37274 39384 44655 49919 44440

Month 2001 2002 2003 2004 2005 2006 2007 January 4589 3920 7237 6831 7198 11465 17511 February 4451 3177 6952 6034 6048 10266 15680 March 3135 2839 3796 5137 5239 7757 11848 April 2745 2305 2209 2837 2927 5014 7659 May 2456 1667 1545 1486 2316 3646 5570 June 1126 1265 1704 1193 2022 2815 4299 July 789 697 2432 2047 2528 3270 4995 August 1457 1558 2565 2951 3444 4611 7043 September 1142 1289 2074 2295 2517 3587 5480 October 1254 1618 2089 3170 5210 5137 7846 November 2441 3815 4161 5367 7315 8894 13585 December 4115 6209 6002 6726 9504 12536 19147 Total 29700 30359 42766 46074 56268 78998 120663 Monthly distribution for 2006 and 2007 are estimates

161

Table 4.12: Seasonal indices for tourist arrivals in Kovalam Month 1988 1989 1990 1991 1992 1993January 183 182 163 166 152 126February 136 144 135 129 129 112March 94 109 107 105 93 95April 51 60 65 75 80 78May 29 34 57 56 64 62June 21 27 45 45 63 57July 42 52 59 65 56 69August 76 75 82 75 93 95September 34 49 80 84 90 93October 148 124 119 106 112 113November 180 159 127 129 130 133December 192 170 161 164 138 165Month 1994 1995 1996 1997 1998 1999 2000January 143 174 155 181 176 156 134February 122 149 140 152 140 121 144March 94 133 175 159 140 120 68April 65 79 98 67 79 88 86May 50 54 23 49 67 80 110June 62 33 14 38 52 61 47July 57 61 32 34 59 78 44August 63 98 69 54 71 84 99September 196 96 68 50 63 75 99October 186 90 102 68 75 87 81November 64 110 157 167 134 119 139December 98 123 167 181 145 131 149

Month 2001 2002 2003 2004 2005 2006 January 148 184 215 187 184 200 February 150 149 199 166 153 177 March 112 133 107 140 132 131 April 104 107 61 76 72 84 May 100 75 42 39 55 61 June 48 53 47 31 46 45 July 35 27 67 52 54 50 August 67 54 72 74 68 66 September 54 42 58 58 47 49 October 60 52 57 80 95 67 November 119 123 112 133 130 113 December 203 200 163 164 166 157

162

Figure 4.8: Pattern of changes in seasonal indices with respect to foreign tourist arrivals in

Kovalam

163

Table 4.13: Monthly variation in tourist arrivals at Kovalam Variation in number of times Variation in absolute numbers 1990 to

1995 1995 to

20002000 to

20051990 to

19951995 to

2000 2000 to

2005 January 0.89 1.03 1.4 -630 134 2074 February 0.94 1.23 1.12 -281 1010 630 March 1.04 0.66 2.02 157 -1326 2650 April 0.97 1.47 0.9 -71 1032 -321 May 0.76 2.74 0.56 -469 2637 -1840 June 0.62 1.88 1.12 -582 841 224 July 0.9 0.91 1.53 -194 -154 881 August 1.04 1.28 0.94 112 789 -210 September 1.07 1.29 0.69 195 818 -1132 October 0.69 1.1 1.75 -1209 261 2232 November 0.79 1.51 1.47 -891 1687 2329 December 0.68 1.44 1.83 -1688 1588 4311

iii. Tourist projections for Kovalam

The increase in tourist arrivals in 2007 has greatly influenced in finding the best fit for

a curve to represent the trend at Kovalam. If this latest figure is excluded, the best fit

is a Sinusoidal curve with ups and downs. As can be seen in Figure 4.9, the scatter plot

of monthly tourist arrivals break the up and down characteristics by around 2005 and

instead of coming down as in the case of a Sinusoidal fit, the actual arrivals have gone

up. It could be gathered from the field that new investments are taking place for

developing properties by the private sector. The speculations and the activities favour

the present change in the trend of tourist arrivals to continue. The best fit obtained for

Kovalam is also a 4th degree polynomial and the estimated model is as follows:

Y = 3634.8925 – 37.604904 x + 0.9643561 x2 – 0.0082654521 x3 + 2.2203759 e-005 x4

(Standard error = 559.3619710, Correlation coefficient = 0.8243363), where Y is the

number of foreign tourist arrivals at Kovalam and x is the time variable. Value of x is

the serial number of months in a year with the value 1 for January 1988. The seasonal

164

indices for the months in 2006 are applied on the de-seasonalized projection figures

obtained from the model and the tourist arrivals for the three years from 2008 are

estimated as given in Table 4.14.

Any decrease in tourist arrivals in 2008 will make the model unfit. Because of the

volatile behaviour of tourist arrivals experienced hitherto, it is necessary to update the

model using the latest arrival figures. According to the figures arrived at here,

Kovalam is poised for a moderate growth of tourist arrivals in 2008 and a growth

above 30% in 2009 and 2010.

Table 4.14: Estimated tourist arrivals to Kovalam Month 2008 2009 2010January 19578 25934 34146February 17739 23491 30908March 13442 17794 23395April 8824 11677 15341May 6561 8678 11391June 4955 6551 8592July 5636 7448 9761August 7616 10058 13172September 5788 7641 9996October 8102 10688 13972November 13986 18439 24085December 19890 26206 34199Total 132117 174605 228958Growth rate 9.49 32.16 31.13

165

iv. Identification of life cycle

As it can be seen from the scatter plots made for Kovalam, the life cycle goes through

periods of decline before being rejuvenated and achieve new growth. A similar

pattern is identified by Groucutt, Leadley and Forsyth (2004). Reasons for the

rejuvenation according to the authors could be due to an improved product

formulation or modification or new packaging. The growth which started in 2001

after a decline is continuing in the case of Kovalam. In order to arrive at a conclusion

on the stage of the life cycle of Kovalam, various characterisitcs that appear in the life

cycle are explored below, as it was done for Kerala tourism.

Sales: The tourist arrivals was at its peak in 2007. The growth in tourist arrivals from

2004 to 2005, 2005 to 2006 and 2007 were remarkable with growth rates at 22.13%,

40.4% and 52.74%. But for these growths in the recent years, tourist arrival figures at

S = 559.36197100r = 0.82433635

Months starting from Jan 1988

Tour

ist a

rriv

als

1 13 25 37 49 61 73 85 97 109 121 133 145 157 169 181 193 205 217 229 2411431

2623

3814

5006

6198

7389

8581

Figure 4.9: Scatter plot of de-seasonalised tourist arrivals and the polynomial curve showing the foreign tourist arrival pattern at Kovalam

166

Kovalam was fluctuating from about 30000 tourists to 50000 tourists a year. The first

sign of breaking this upper limit was seen in 2005 and in 2007 it hit an all time high

and crossed the one lakh mark. This can be interpreted as the rejuvenation stage as

described by Butler (1980). The forecasts also indicate maintaining of higher growth

rates, but less than that recorded in 2006 and 2007.

Year Growth rate (%)1989 7.661990 -0.331991 -1.21992 14.011993 -2.111994 -37.161995 24.621996 6.121997 5.661998 13.381999 11.792000 -10.982001 -33.172002 2.222003 40.872004 7.742005 22.132006 40.42007 52.74

Customers and market: In true reflection of the pattern for India as well as for Kerala,

Kovalam also attracts maximum number of tourists from Europe, dominated by UK

nationals (Table 4.15).The Asia and Pacific, and America markets were showing signs

of consolidation with 15 to 20% of the total market share till 2003. Tourists from Asia

and Pacific markets were more or less steady with about 50000 arrivals a year. The

arrivals from this market stood at 75000 in 2007. Tourists from American region was

steady at around 35000 mark a year till 2006. In 2007, the arrivals from America

crossed 50000. Kovalam crossed the one lakh mark greatly because of the increased

167

tourist inflow from Europe, especially UK and France. The increased arrivals from

Europe was about 50000 tourists in 2007 alone.

Table 4.15: Market share of world tourism markets at Kovalam (%)

Year Europe Asia and

Pacific America AfricaMiddle

East Total1996 68 24 7 0 1 1001997 65 27 7 0 1 1001998 62 26 9 0 2 1001999 60 26 11 0 3 1002000 41 41 16 0 1 1002001 55 26 18 0 1 1002002 71 11 17 1 1 1002003 71 15 11 1 2 1002004 76 12 11 1 1 1002005 76 12 9 1 2 1002006 75 11 10 1 4 1002007 83 6 7 1 3 100

Competitors: The six destinations – Kochi, Kovalam, Thekkady, Munnar, Alappuzha

and Kumarakam – account for about two-third of the foreign tourist arrivals in the

State. In terms of number of tourists, these can be termed as the competing

destinations within the State. Among these, Kochi, Kovalam and Alappuzha have

coastal line. But both Kochi and Alappuzha are known for their backwaters. As such,

for the class of a destination like Kovalam, there exists no competition from the other

five in the top six destinations. The primary survey conducted at Kovalam reveals the

name of Varkala as a competing upcoming destination for Kovalam. There are other

destinations being developed within the State in the north. Thus, though Kovalam is

to compete with destinations of other types, few of the new destinations offer

attractions similar to that of Kovalam. The foreign tourist arrivals at the competing

destinations inside Kerala are given in Table 4.16.

168

Table 4.16: Number of foreign tourists in the competing tourist destinations in Kerala Sl

No Tourist site 2000 2001 2002 2003 2004 2005 2006 2007

1 Kochi city 51726 65406 83626 94445 106427 105665 119310 1258532 Kovalam 44,440 29700 30359 42766 46074 56268 78999 1206633 Thekkady 21543 17258 16386 22747 28884 27061 31930 300384 Munnar 7679 6944 8900 11414 11654 90375 Alappuzha 12013 12871 17261 26157 38024 30274 36407 315036 Kumarakom 8477 9099 16820 16608 21097 18410

Total 129722 125235 163788 202158 245129 247290 299397 335504All Kerala 209933 208830 232564 294621 345546 346499 428534 515808

Share in State total (%) 61.79 59.97 70.43 68.62 70.94 71.37 69.87 65.04

Source: Tourist Statistics (various years), Department of Tourism, Government of Kerala

4.2.3. Thekkady 

i. Growth of tourism

Thekkady is popular as a hill resort among tourists and is the location of the Periyar

National Park. A s a natural wildlife sanctuary, Thekkady has a history dating back to

the year 1934. It is home to herds of elephants, sambar, tigers, gaur, lion-tailed

Macaques and Nilgiri Langurs. The Periyar wild life sanctuary is spread across 777

sq. km area, of which 360 sq.km is thick evergreen forest (Department of Tourism,

2006). This sanctuary was declared as a Tiger Reserve in 1978. The park is also often

called by the name Thekkady. Thekkady is famous for natural spices like black

pepper, cardamom, cinnamon and clove.

The splendid artificial lake formed by the Mullaperiyar Dam across the Periyar River

– the Periyar reservoir - adds to the charm of the park, and the area of this lake is 26

sq.km (District Tourism Promotion Council Idukki, 2007). Thekkady is located

around Periyar reservoir. The dam gets the name because of its location in the

confluence of Mullayar and Periyar rivers.

169

Besides the natural attractions, history also has played its part in the evolution of

Thekkady as a tourist destination. The Mullaperiyar dam was conceived by the British

during the colonial rule to divert the waters of the west-flowing Periyar river

eastwards. The dam was built by the British Army Engineering Corps. The first dam

was washed away by floods, and a second masonry dam was constructed in 1895. The

historical events that followed after the construction of the dam in 1895 are as

follows:

Though efforts are made to protect the wild life and shield them from human

interference, there are instances of struggles against illegal encroachments by the tiger

and elephant poachers, and cultivators of cannabis. Tourist entry to the Periyar

National Park is restricted to the northern corner adjacent to the Periyar Lake. The

core zone of the park is not accessible to tourists. Out of a total area of 430 sq. km

termed as the buffer zone, only 55 sq.km area is kept apart for tourism. The famous

Sabarimala temple is located in the buffer zone. This temple is visited by more than 4

million pilgrims in a year.

1899 •The Periyar Lake Reserve formed

1933 •SCH Robinson made the first game warden

1934 •Nellikkampetty Game Sanctuary formed

1950 •Periyar was declared a wild life sanctuary

1978 •Periyar was declared a Tiger Reserve

1982 •The core area of the park notified as a National Park

1991 •Thekkady brought under "Project Elephant"

1996 •India eco-development project launched

2001 •Reorganisation of the area - Periyar East and Periyar West

170

The tourist season at Thekkady is from September to May. Main tourism activities at

Thekkady are boating, elephant riding and guided trekking. Eco-tourism programs are

also organized that includes, nature walk, tiger trail, border hiking, bamboo rafting,

jungle petrol, tribal heritage, jeep safari, jungle camp, Coracle river rafting and

bullock cart ride. Spice plantation tours and Kathakali dance performances are also

organized for the tourists.

Thekkady was in the first three tourist destinations in Kerala in terms of the number

of foreign tourist arrivals. Backwater tourism at Alappuzha and Kumarakom, have

started attracting tourists especially from the beginning of this century. Munnar

became a hotspot for domestic tourists. All these resulted in reduced growth of

foreign and domestic tourists visiting Thekkady. The foreign tourist arrivals for the

years from 1988 to 2007 are given in Table 4.17. It can be seen that there are ups and

downs in the trend of foreign tourist arrivals at Thekkady. In the beginning of the

nineties, the number of tourist arrivals was around 16000 a year, but it came down to

around 12000 by the end of the same decade. The growth in Kerala tourism in this

century also has helped Thekkady to take the arrivals to around 30000 a year by 2006.

ii. Seasonal characteristics

September to May is considered the best season for tourists. December and January

were the most favoured months more than ten years back. This is now getting

changed to January and February as can be seen in the seasonal indices worked out

for Thekkady. The months from October to March can be treated as the peak season

for tourists coming to Thekkady. The seasonal indices for foreign tourist arrivals at

Thekkady are given in Table 4.18. The first quarter of the year shows an increasing

trend in the values of seasonal indices. All the three months in the second quarter have

171

shown a declining trend in the values of the seasonal indices. September in the third

quarter and November in the fourth quarter have seen the values of the seasonal

indices rising. The shifting trend in the seasonality of foreign tourist arrivals is shown

in Figure 4.10. Monthly variations in tourist arrivals for the years from 1990 to 1995,

1995 to 2000 and from 2000 to 2005 are given in Table 4.19. During 1990 to 1995, the

tourist arrivals declined in all the 12 months, by half or less than half, mostly due to

the decline in tourist arrivals recorded in 1994 and 1995. There was a complete

reversal from 1995 to 2000. The upward trend continued for the months from October

to April from 2000 to 2005.

iii. Tourist projections for Thekkady

The ups and downs in the tourist arrivals have reflected in the best fit arrived at to

show the trend in Thekkady. The best fit obtained is a 4th degree polynomial and the

estimated model is as follows:

Y = 687.32275 + 45.268862 x – 0.93424222 x2 + 0.0062661271 x3 – 1.2634438 e-005 x4

(Standard error = 267.4002163, Correlation coefficient = 0.8949497), where, Y is the

number of foreign tourist arrivals and x is the serial number of months in a year with

the value 1 for January 1988. As can be seen in Figure 4.11, the latest declining trend

has started in the year 2006. Using the model, the estimated tourist arrivals for the

three years, 2008 to 2010 are given in Table 4.20.

172

Table 4.17: Monthly tourist arrivals at Thekkady Month 1988 1989 1990 1991 1992 1993 January 1530 2490 2166 2143 2211 1891 February 1129 1980 1807 1672 1898 1690 March 780 1516 1448 1355 1398 1433 April 424 836 882 974 1222 1170 May 235 462 766 717 984 914 June 168 360 593 581 976 841 July 341 689 769 856 862 1007 August 638 988 1061 995 1415 1333 September 419 822 1016 1126 1368 1256 October 1286 1623 1513 1427 1720 1455 November 1587 2108 1615 1767 1993 1650 December 1701 2291 2040 2291 2113 1999 Total 10238 16165 15676 15904 18160 16639

Month 1994 1995 1996 1997 1998 1999 2000 January 1021 913 1218 2406 1689 972 1978 February 825 807 1512 1783 1236 688 2986 March 620 717 1800 1485 999 512 2416 April 441 406 1001 725 577 428 1149 May 327 278 124 235 216 197 648 June 367 175 68 282 284 285 543 July 330 330 315 359 539 718 654 August 379 524 1026 815 1092 1368 2216 September 1251 518 452 460 815 1169 1978 October 1232 497 564 721 808 894 1437 November 427 604 1251 1130 1364 1598 2864 December 661 660 1692 1653 1676 1698 2674 Total 7881 6429 11023 12054 11295 10527 21543

Month 2001 2002 2003 2004 2005 2006 2007 January 3009 2584 3866 5204 4286 5386 5067 February 4026 3091 3569 5715 4220 5861 5514 March 2482 1947 2120 2824 3352 3617 3403 April 1060 1181 1284 260 1425 1481 1393 May 555 234 534 576 566 701 659 June 86 66 307 260 290 287 270 July 351 327 722 1168 983 1009 950 August 1104 1267 1312 3121 1675 2410 2267 September 1125 1171 1223 115 1200 1374 1293 October 658 1128 1667 1901 1965 2080 1957 November 1473 1579 3097 4195 4009 4080 3838 December 1329 1811 3046 3545 3090 3644 3428 Total 17258 16386 22747 28884 27061 31930 30039 Monthly distribution in 2006 and 2007 are estimates

173

Table 4.18: Seasonal indices for tourist arrivals in Thekkady Month 1988 1989 1990 1991 1992 1993 January 196 202 162 167 150 119 February 145 157 135 130 127 107 March 101 117 107 105 92 91 April 55 63 65 76 79 75 May 31 34 58 56 63 60 June 23 25 46 45 62 56 July 44 48 60 65 56 69 August 77 70 83 75 93 96 September 47 59 80 84 90 96 October 138 116 119 105 114 117 November 167 149 127 129 132 139 December 176 160 160 163 141 176 Month 1994 1995 1996 1997 1998 1999 2000 January 116 172 155 222 177 151 133 February 100 150 188 166 127 104 196 March 79 139 218 139 99 75 151 April 57 87 121 68 56 62 69 May 45 62 14 22 21 28 37 June 58 39 7 26 27 40 30 July 57 71 31 35 53 96 34 August 66 105 94 83 113 159 110 September 217 92 41 49 89 116 96 October 213 80 53 80 91 82 70 November 74 95 118 126 156 141 140 December 117 106 158 184 191 147 132

Month 2001 2002 2003 2004 2005 2006 January 175 206 235 227 133 207 February 241 246 215 239 135 222 March 156 154 127 116 108 135 April 69 92 76 11 45 55 May 38 18 30 24 18 26 June 6 5 16 10 9 11 July 27 23 36 47 34 37 August 90 86 61 131 71 89 September 96 78 54 5 62 51 October 57 74 74 78 118 78 November 128 103 139 170 259 153 December 117 116 137 143 206 137

174

Table 4.19: Monthly variation in tourist arrivals at Thekkady Variation in number of times Variation in absolute numbers

1990 to 1995

1995 to 2000

2000 to 2005

1990 to 1995

1995 to 2000

2000 to 2005

January 0.42 2.17 2.17 -1253 1065 2308February 0.45 3.7 1.41 -1000 2179 1234March 0.5 3.37 1.39 -731 1699 936April 0.46 2.83 1.24 -476 743 276May 0.36 2.33 0.87 -488 370 -82June 0.3 3.1 0.53 -418 368 -253July 0.43 1.98 1.5 -439 324 329August 0.49 4.23 0.76 -537 1692 -541September 0.51 3.82 0.61 -498 1460 -778October 0.33 2.89 1.37 -1016 940 528November 0.37 4.74 1.4 -1011 2260 1145December 0.32 4.05 1.16 -1380 2014 416

175 C

urve fit and projections for Thekkady The best fit obtained is a 4

th degree polynomial and the estim

ated model is as follow

s: Y

= 687.32275 + 45.268862 x – 0.93424222 x2 + 0.0062661271 x

3 – 1.2634438 e -005 x

4 (Standard error = 267.4002163, C

orrelation coefficient =0.8949497 ) W

here, Y is the num

ber of foreign tourist arrivals and x is the serial number of m

onths in an year w

ith the value 1 for January 1988. Using the m

odel, the estimated tourist arrivals for the

three years from 2008 are given below

. Seasonal index for 2006 is used for projections in 2008, 2009 and 2010. M

onth 2008

20092010

Januar y 5020

42461984

February 5335

44562855

March

32132647

2904April

12951052

1666M

ay 606

484636

June 253

199280

July 840

650109

August

19931513

337S

eptember

1125836

732O

ctober 1692

1232373

Novem

ber 3262

2318498

Decem

ber 2866

1984829

Total 27500

2161713203

Grow

th rate -8.45

-21.39-38.92

Destination experience

Nationality and daily expenditure

Figure 4.10: Pattern of changes in seasonal indices with respect to foreign tourist arrivals in

Thekkady

176

Table 4.20: Estimated foreign tourist arrivals at Thekkady Month 2008 2009 2010January 5020 4246 1984February 5335 4456 2855March 3213 2647 2904April 1295 1052 1666May 606 484 636June 253 199 280July 840 650 109August 1993 1513 337September 1125 836 732October 1692 1232 373November 3262 2318 498December 2866 1984 829Total 27500 21617 13203Growth rate -8.45 -21.39 -38.92

S = 267.40021627r = 0.89494970

Months starting from Jan 1988

Tour

ist

Arri

vals

0 12 24 36 48 60 72 84 96 108 120 132 144 156 168 180 192 204 216 228 240 252220

676

1132

1588

2043

2499

2955

Figure 4.11: Scatter plot of de-seasonalised tourist arrivals and the polynomial curve showing the foreign tourist arrival pattern at Thekkady

177

iv. Identification of life cycle

The past history of tourist arrivals to Thekkady shows the fluctuations in demand.

And as the scatter plots indicate, the ups and downs are expected to continue. Though

a linear trend would show an increasing trend, the model that is developed for

Thekkady predicts decline in tourist arrivals in the three years from 2008 to 2010. The

various characteristics that appear in the life cycle stages are discussed below before

attempting to identify the present stage of Thekkady in the life cycle.

Sales: The tourist arrivals to Thekkady were at its peak in 2006. But the highest

growth rates were during the recoveries made during 1989, 1996, 2000 and 2003. The

trend of upward and downward swing observed in the past has influenced the

forecasts to predict a downward trend in the tourist arrivals in the coming three years.

Year Growth1989 57.891990 -3.031991 1.451992 14.191993 -8.381994 -52.641995 -18.421996 71.461997 9.351998 -6.31999 -6.82000 104.652001 -19.892002 -5.052003 38.822004 26.982005 -6.312006 17.992007 -5.92

178

Customers and markets: Thekkady also has a similar market as that of Kerala or

Kovalam. The only change is the share of tourists from the Americas. Thekkady has

an edge over Kovalam in the share of American tourists. The four countries that held

the major share of foreign tourists at Thekkady are UK, France, USA and Germany

(Table 4.21). Thekkady is seen as the second preferred destination in Kerala for the

tourists from France.

Table 4.21: Market share of world tourism markets at Thekkady

Year Europe Asia and

Pacific America AfricaMiddle

East Total 1996 80 12 7 0 1 100 1997 87 5 7 0 0 100 1998 85 6 8 0 0 100 1999 83 8 8 0 1 100 2000 77 11 10 0 1 100 2001 81 8 10 0 1 100 2002 86 6 7 0 0 100 2003 84 5 9 1 1 100 2004 84 6 9 0 1 100 2005 79 7 13 1 1 100 2006 80 5 12 1 1 100 2007 80 6 12 1 1 100

Competition: Among the top six destinations preferred by the foreign tourists,

Thekkady ranks fourth. Munnar is another hill resort in very close proximity to

Thekkady. In the domestic tourism market, Munnar attracts 1.5 times the number

domestic tourists who come to Thekkady. Other than the pilgrim centres, Wayanad is

another destination that competes with Thekkady in the domestic tourism front.

179

4.3. Measurement of factors that influence the life cycle

The factors that influence the life cycle of the destinations are identified as follows in

Chapter 3:

Each of these factors is discussed with the help of secondary information and the

primary surveys conducted at Kovalam and Thekkady. All these factors are discussed

with respect to the two destinations only.

4.3.1. Destination experience

The components of destination experience taken into account in the research work

returned the values as given in Table 4.22. It can be seen that the destination

experience was higher in the case of Thekkady compared to Kovalam. Overall

destination experience of tourists at Thekkady was 70% and at Kovalam this was

67%. The hospitality component of the destination experience was higher at Kovalam.

i. Destination Experience

ii. Quality of Resources

iii. Attitude of Residents

iv. Natural Ambience of the Site

v. Urbanisation

vi. Commercial Land Use

vii. Transition from Tourism

viii. Local Participation

ix. Occupancy of Tourist Accommodation

x. Historicity

xi. Tourism Promotion

180

The environment component is seen to have adversely affected the destination

experience index of tourists at Kovalam.

Table 4.22: Estimated index of destination experience Sl No Component Median Range Satisfaction

index Kovalam 1 Tourist expectations 3.67 1.33 to 5 73.33 2 Tourism environment 2.00 1 to 5 40.00 3 Hospitality 3.33 2 to 5 66.67 Overall destination experience 66.67 Overall destination experience (weights applied) 66.67 Thekkady 1 Tourist expectations 4.00 1 to 5 80.00 2 Tourism environment 4.00 1 to 5 80.00 3 Hospitality 3.33 2.33 to 5 66.67 Overall destination experience 68.89 Overall destination experience (weights applied) 70.00

4.3.2. Quality of resources 

Education as well as skill of resources, engaged in tourism industry, is vital.

Employers use educational attainments as an indication of desirable personal and

work attributes (Vijayakumar & Pillai, 2008). In the survey conducted by

Vijayakumar and Pillai (2008) in the three destinations – Kovalam, Kumarakom and

Thekkady - in Kerala, it was found that only 7% of the sample respondents drawn

from the hotel industry were having education below 10th Standard. The largest

category of employees (37%) were having plus two (12th Standard) qualification. Post

graduates and graduates were respectively 10% and 33%. The survey also showed

that 33% of the respondents had undergone formal training in tourism related courses.

Majority of the respondents who lacked formal professional qualification were above

35 years of age. The hotel industry generally preferred formally trained people in food

production and food and beverages services (Vijayakumar & Pillai, 2008).

181

Besides the employees in the accommodation sector, the tourists come across people

who are in tourism-related services like taxi drivers and houseboat operators. Kerala

Institute of Tourism and Travel Studies (KITTS), the educational institute under

Department of Tourism, Government of Kerala, organises training programmes

regularly as part of building a favourable attitude towards the development of tourism

in Kerala. The details of training programmes organized by KITTS during the years

2002-03 to 2007-08 are given in Table 4.23.

Table 4.23: Training programmes organised by KITTS during 2002-03 to 2007-08 Participants of training / orientation programmes

2002-03

2003-04

2004-05

2005-06

2006-07

2007-08

Home stay Owners 54 400Guest House Managers 13 Tourist Police 175 55 VHSE Teachers 13 Tourist Taxi Drivers 66 52 265 635Teacher Coordinators of Tourism Clubs 257 283 41

39

Tourist Guides 36 5 12 35 35Tourist Information Personnel 36 42 Unemployed youth 16 DTPC employees 33 14 Telephone operators 4 6 Bank staff (Customer service) 25Life guards 45 160 110Travel / tour executives 20 20Front desk agents in hotels 32 Houseboat crews 25 172 EDC members 43 50 Vana Samrakshana Samithi volunteers 30 42 90 127Masseurs 51 Students 10 103 196 390 150 Total participants 624 527 377 808 825 1352Source: Compiled from KITTS and Annual Reports of KITTS

The objective of conducting these training programmes was to make a visitor-friendly

society by way of attitudes and service quality. In the field of hospitality education,

182

institutes in the private and public sector contribute to meet the human resource

requirement. Department of Tourism, Government of Kerala, has a system of granting

approval to the courses offered by the private sector1, subject to satisfying specified

norms to ensure quality. The approval of the courses is granted on the basis of

infrastructure, faculty, syllabus and other facilities like library, computer lab etc.

Conduct of the programmes right from admission to examination are by the

institutions themselves. Besides Government of Kerala, All India Council for

Technical Education (AICTE) and National Council for Hospitality Management also

approve courses in the hospitality sector and some of the institutions seek approval of

these Councils. Examinations for the courses in hospitality sector by the Food Craft

Institutes in Kerala are conducted by the Technical Education Department of

Government of Kerala. Institute of Hospitality Management and Catering Technology

(IHMCT), Kovalam, which is under Government of India, offers three year degree

courses in hotel management.

While the above efforts are meant for the State as a whole or beyond destination level,

efforts to maintain quality of resources are reflected in the number of quality

resources engaged in tourism activities. Use of trained manpower resources in hotel

industry is extracted through the survey of accommodation facilities in Kovalam and

Thekkady.

The questionnaire given to the hotels and home stays sought information on

employment details. These included total employment (males and females), number

of trained employees and categories of employment. The attempt was to extract the

complete picture of the presence of trained resources in the accommodation industry.

1 Government Orders (Rt) No. 6640/95/GAD dated 19.7.95 and (Rt) No. 189/96/GAD dated 5.1.96

183

Some of the hotels and home stays were reluctant to furnish these details. However,

from the details furnished by 42 establishments, Table 4.24 is generated.

Table 4.24: Percentage of trained employees in the accommodation establishments Sl No.

Destination Number of establish-ments responded

Number of employees Number of trained employees

Percent of trained employees

Males Females Total Males Females Total 1 Kovalam 13 157 22 179 98 13 111 62.01% 2 Thekkady 29 423 83 506 239 37 276 54.55% Total 42 580 105 685 337 50 387 56.50%

These proportions are tested using the test statistics z to confirm whether the inference

could be made that the destinations have higher share of quality resources. The null

hypothesis and the alternate hypothesis stated are:

Ho: p = 0.5

H1: p > 0.5

With the values of p=0.5, q=0.5, n=13 and observed value p=0.6201 at Kovalam, the

test statistic z= 0.866. At 5% level of significance, Ho will be rejected if z > 1.645, the

normal curve area table value of z in the case of one-tailed test (right tail). Since the

calculated value of z is only 0.866, the null hypothesis is accepted. Hence it cannot be

claimed that the proportion of quality resources is higher at Kovalam.

In the case of Thekkady, n=29 and observed value of p=0.5455. The z value here is

0.49. Here also, the null hypothesis is accepted and hence it cannot be claimed that the

proportion of quality resources is higher at Thekkady.

A comparison with the findings of the study by Vijayakumar and Pillai (2008) may

not be possible because the present survey sought information on industry related

training and not level of education. But it can be safely concluded that most of the

184

employees in the accommodation industry at Kovalam and Thekkady have education

level at High School level.

The desirable situation is when all the resources engaged have undergone training.

Thus the measure of this factor can have a maximum value of 100, if expressed in

percentages. The values of this measure are taken as the percentage of trained

employees as observed in the sample. Thus the values of quality of resources

measured are 62 and 55 for Kovalam and Thekkady respectively.

4.3.3. Attitude of residents 

The attitude variables measured in the survey are grouped using Cluster analysis so

that the attitude measure could be separately made for these groups. Specifying the

number of clusters to 3, the following clusters emerged from the sample. Out of the

three clusters, Cluster 1 clearly is the set of variables that indicates the benefits and

variables in Cluster 2 reflect the apprehensions or concerns as perceived by the

residents. Hence these two clusters are named as Satisfiers and Repellents. There are

two variables in Cluster 3 that are neither benefits nor apprehensions, but give a

conservative or critical outlook of tourism. Hence this cluster is given the name

“Disappointers”. The clusters and the variables grouped under are given below:

185

Satisfiers (Cluster 1)

•Tourism attracts more spending and investment in Kovalam / Thekkady•Tourism encourages cultural activities and art forms •The overall benefits of tourism outweigh the negative impacts•The tourism industry provides many worthwhile employment opportunities for the people in Kovalam / Thekkady

•The development of tourism business will have an impact on the land value. •Tourism enhances the quality of life of people in Kovalam / Thekkady•Tourism holds great promise for the people in Kovalam / Thekkady•Because of tourism, there are more parks and other recreational facilities that local residents can use

•Tourism is one of the brightest spots in the economic future of Kovalam / Thekkady•The household standard of living is higher because of money that tourists spend here•The environmental impacts resulting from tourism are relatively minor•Tourism is responsible for too fast a rate of urbanization in Kovalam / Thekkady

Repellants (Cluster 2)

•Tourists add greatly to the traffic problems in Kovalam / Thekkady•The more the number of tourists who come to Kovalam / Thekkady, the harder it is for the people in the locality

•Tourism disrupts the tranquility•The local residents are the ones who really suffer from living in an area popular with tourists

•Tourists should be taxed more than citizens for the services they use. •Most of the money earned from tourism flows out-of-State companies•Tourists do not pay their fair share for the services communities provide•Tourists crowd out local residents in many good hunting and fishing spots•An increase in tourists in Kovalam / Thekkady will lead to friction between local residents and tourists

•Tourism has increased the number of crime-related problems in Kovalam / Thekkady•It’s okay to charge tourists more •Tourists create a burden on the services in Kovalam / Thekkady•Tourism development in Kovalam / Thekkady needs to be discouraged•Do you think that Kovalam / Thekkady has a negative image for tourists?

Disappointers (Cluster 3)

•The problem with tourism is that most of the jobs in the tourism industry are low paying•Only a small minority of the people in Kovalam / Thekkady benefits economically from tourism

186

All the variables under Clusters 2 and 3 are considered as reversal items for extracting

the score. Attitude of residents towards these clusters are estimated for the following

classifications of the residents:

• All residents together

• Residents having no interaction with tourists

• Residents having some interaction with tourists, and

• Residents having high interaction with tourists.

Summative score is taken as the measure of attitudes. The frequency distributions of

the summative scores are derived for the attitude groups. Frequency of the sample

units that favour development of tourism in the destination is made from the

summative scores. One attitude variable takes the values 1 to 5, with the score 1

reflecting negative attitude and the score 5 reflecting the positive attitude. The scores

4 and 5 reflect favourable attitude. The scores 1 and 2 reflect negative attitude,

whereas the score 3 is neutral. The scores 4 and 5 are clubbed together to find the

frequency of sampling units that favours tourism and scores 1 to 3 are clubbed to form

rest of the sample. Since summative scores are used, such a regrouping needs an

explanation before getting the frequency table in the regrouped format. For example,

there are 12 variables that form the attitude group ‘Satisfiers’. Here, the score of

sample units that favour tourism would be 12 x4 = 48 and above. When 3 is taken as

the upper limit score of the other group, 12 x 3 = 36 would be the summative score

that limits this group. Because summative scores are taken, there would be scores

between 36 and 48. Hence the midpoint of 36 and 48, i.e., 42 is taken as the score that

divides the sampling units into ‘favourable’ and ‘others’. The measured values for

Kovalam are given in Table 4.25.

187

Table 4.25: Distribution of residents of Kovalam according to the attitudes Attitude variable Group  Favourable  Others  Total 

Proportion favourable 

All samples 

Satisfiers  136  45  181  75.14% 

Repellents  91  90  181  50.28% 

Disappointers  16  165  181  8.84% 

Sample with no interaction with tourists 

Satisfiers  28  8  36  77.78% 

Repellents  19  17  36  52.78% 

Disappointers  13  23  36  36.11% 

Sample with low interaction with tourists 

Satisfiers  49  21  70  70.00% 

Repellents  34  36  70  48.57% 

Disappointers  33  37  70  47.14% 

Sample with high interaction with tourists 

Satisfiers  59  16  75  78.67% 

Repellents  38  37  75  50.67% 

Disappointers  21  54  75  28.00% 

It is also tested whether the favourable attitude towards tourism is independent of the

residents grouped according to the intensity of interaction with tourists. This is tested

using Chi-square statistic and the calculated values of Chi-square are given in Table

4.26. At 5% significance level, value of Chi-square for degrees of freedom 2 is 5.991.

Table 4.26: Chi-square values to test association of favourable attitude and resident groups at Kovalam

1 Satisfiers Interaction level

(Observed values) Interaction level

(Expected values) Chi-square values

Nil Low High Total Nil Low High Total df = 2 Favourable 28 49 59 136 27 53 56 136 1.623414Others 8 21 16 45 9 17 19 45

36 70 75 181 36 70 75 181 2 Repellents

Favourable 19 34 38 91 18 35 38 91 0.176068Others 17 36 37 90 18 35 37 90

36 70 75 181 36 70 75 181 3 Disappointers

Favourable 13 33 21 67 13 26 28 67 5.706721Others 23 37 54 114 23 44 47 114

36 70 75 181 36 70 75 181

188

For all the three sets of variables, the calculated values of Chi-square are less than the

table value and hence the null hypothesis is accepted. Thus it can be inferred that the

favourable attitude of residents of Kovalam are independent of the resident groups

giving their level of interaction with tourists.

Measured values of attitude of residents at Thekkady are given in Table 4.27.

Table 4.27: Distribution of residents of Thekkady according to attitudes

Attitude variable Group Favourable Others Total Proportion favourable

All samples Satisfiers 94 45 139 67.63% Repellents 111 28 139 79.86% Disappointers 14 125 139 10.07%

Sample with no interaction with tourists Satisfiers 13 18 31 41.94% Repellents 20 11 31 64.52% Disappointers 17 14 31 54.84%

Sample with low interaction with tourists Satisfiers 44 15 59 74.58% Repellents 51 8 59 86.44% Disappointers 20 39 59 33.90%

Sample with high interaction with tourists Satisfiers 37 12 49 75.51% Repellents 40 9 49 81.63% Disappointers 22 27 49 44.90%

The exercise carried out for Kovalam to test the significance of the attitudes shown is

repeated for Thekkady and the calculated z-values are given in Table 4.27. Residents

having no interaction with tourists do not carry a positive attitude towards

development of tourism at Thekkady. Unlike Kovalam, Thekkady is also a spice

trading centre. Even in the core tourism area at Thekkady, there are households who

are ignorant of the positive or negative impact of tourism due to the possible reason of

engaging themselves in non-tourism related sectors. Except for this group, the

189

proportion of residents favouring tourism development is higher and shows a positive

attitude in ‘satisfiers’ and ‘repellents’ groups.

It is also tested whether the residents of Thekkady favour tourism development

irrespective of their level of interaction with the tourists. The null hypotheses for all

the three resident groups are rejected (Table 4.28). This is in contrast to the attitude of

residents of Kovalam. The favourable attitude of residents is not independent of the

resident groups.

Table 4.28: Chi-square values to test association of favourable attitude and resident groups at Thekkady

Interaction level (Observed values)

Interaction level (Expected values)

Chi-square values

Nil Low High Total Nil Low High Total df = 2 1 Satisfiers

Favourable 13 44 37 94 19 36 39 94 15.29263 Others 18 15 12 45 9 17 19 45

31 59 49 139 28 54 58 139 2 Repellents

Favourable 20 51 40 111 22 43 46 111 9.113295 Others 11 8 9 28 6 11 12 28

31 59 49 139 28 54 58 139 3 Disappointers

Favourable 17 20 22 59 12 23 24 59 6.425818 Others 14 39 27 80 16 31 33 80

31 59 49 139 28 54 58 139

The index values for the attitude of residents of Kovalam and Thekkady are given in

Table 4.29. Reversal scales are applied to the variables that expressed the

apprehensions or concerns towards development of tourism in their destinations. The

index value hence has to be seen as absence of apprehensions. Ideally, the index

values have to be 100 in all the cases if the entire community supports development of

tourism. The residents at Thekkady, who do not have any interaction with tourists, do

190

not have a favourable attitude towards tourism development as shown in the test

results. The indices are taken as a measure of attitude of residents.

Table 4.29: Index values for the attitude of residents

Sample Group Attitude Group Satisfiers Repellents Disappointers

Kovalam Thekkady Kovalam Thekkady Kovalam Thekkady All residents 75 68 50 80 9 10 No interaction group 78 42 53 65 36 55

Low interaction group 70 75 49 86 47 34

High interaction group

79 76 51 82 28 45

4.3.4. Natural ambience of the site 

It is necessary that the natural ambience of the site remains suitable for tourism. An

assessment of the physical environment of the core tourism area of approximately 3

sq. km surrounding the beaches of Kovalam is available (Committee on Scientific

Study of Kovalam, 2002). The major sources of air pollution were the vehicular

traffic, diesel generator sets in hotels, resorts and shops, household chulas and

outboard engines of boats. The area is free from any major industrial units. The main

sources of noise in the area were from the settlements and commercial establishments

in and around the beach besides the traffic noise. The roaring of the sea, chirping of

birds and rustling of leaves also contributed to the noise level. The ambient air quality

and noise level standards recommended by the Central Pollution Control Board

(CPCB) are given in Table 4.30.

191

Table 4.30: Ambient air quality and noise level limits recommended by Central Pollution Control Board

Ambient air quality Ambient noise level Primary air pollutants

For residential and rural areas (mg / cubic metre)

Community noise exposure Leq (dBA)

SO2 80 for 24 hrs Residential area (night time) 55 NO2 80 for 24 hrs Residential area (day time) 45 CO 4000 per hr Silence zone (night time) 50 Silence zone (day time) 40 Source: Committee on Scientific Study of Kovalam, 2002

The air quality parameters and the noise level exposures in the seashore side of

Kovalam were below these limits. The study also brings out the contamination of the

pond and well waters as well as sea water in the area. Dumping of solid wastes

generated from the hotels, shops and houses near the beach area, is a matter of

concern for Kovalam. It is estimated that about 3 to 4 tons of solid wastes are

generated in a day by over 150 hotels, 1800 households and 200 shops in the Kovalam

region.

The study conducted for the Forest Department, Government of Kerala (Equations,

2002), has brought out the threats of sewage, solid wastes and plastics to the lake

ecosystem and the animals inside the Periyar Tiger Reserve at Thekkady.

The primary survey conducted among the tourists as part of this research has

attempted to bring out the opinion of tourists with respect to the natural ambience of

the destinations. Specifically, tourists were asked to rate the present condition of the

destination and the tourist attractions. The results of the survey are presented in Table

4.31.

192

Table 4.31: Opinion of tourists on current condition and attraction characteristics of the destinations

Sl No Opinion Kovalam Thekkady Combined Number % Number % Number %

A Current Condition 1 Coming down 16 3% 33 11% 49 6%2 Steady 81 15% 24 8% 105 13%3 Getting a new life 41 8% 51 17% 92 11%4 Growing 278 52% 90 31% 368 45%5 No opinion 114 22% 97 33% 211 26%

Total 530 100% 295 100% 825 100%B Attraction Characteristics 1 Out of date 20 4% 8 3% 28 3%2 New 24 5% 31 11% 55 7%3 Mix of old and new 335 63% 168 57% 503 61%4 No opinion 149 28% 88 30% 237 29%

Total 528 100% 295 100% 823 100%

Majority of tourists to Kovalam felt, that Kovalam as a tourist destination is growing.

But the same cannot be said to hold good in the case of Thekkady. But the attraction

characteristics in both the destinations are perceived as a mixture of old and new.

It is the presence of tourists on the land that affect the natural ambience of a

destination. Density of tourists on suitable land per day in the peak season is taken as

a measure of this pressure of the tourists. With respect to the suitable land, the

pressure of tourists on the land is given in Table 4.32. Average number of tourists per

day in the month of January is taken to compute the density. The desired density per

hectare at Kovalam is 67 tourists in a day. The same for Thekkady is 50 tourists per

hectare (Chapter 3). The pressure index is computed by taking the ratio of density of

tourists to desired density.

193

Table 4.32: Density of tourists on suitable land per day in peak season Year Density of tourists per hectare

Kovalam Thekkady Foreign tourists

Domestic tourists

All Ambience index

Foreign tourists

Domestic tourists

All Ambience index

2001 12 4 16 23% 11 33 44 88% 2002 10 4 13 20% 10 49 59 117%

2003 18 7 25 38% 14 56 71 141% 2004 17 12 29 43% 20 39 59 117%

2005 18 7 25 37% 16 39 55 110% 2006 29 9 38 57% 20 40 61 121% 2007 44 11 55 82% 19 38 57 113%

4.3.5. Urbanisation / Disappearing rural characteristics 

The land use pattern of Kovalam has undergone changes over the years (Committee

on Scientific Study of Kovalam, 2002). Most of the paddy fields are either reclaimed

or converted for cultivating crops like tapioca, banana, vegetables and coconut, and

for construction of houses. The reason for such a change is attributed to lack of

irrigation facilities, non-availability of laborers and increasing cost of farming. Still,

about 55% of the people are reported to be farmers in Kovalam. The land use pattern

of Kovalam within 500 metres of Coastal Regulation Zone (CRZ) is shown in Table

4.33.

In the case of Thekkady, while the Periyar Tiger Reserve is a protected area, the

impact of tourism to the community is at Kumily. From the serene village in the

Western Ghats bordering the thick forests of the Tiger Reserve, tourism has converted

Kumily into a township (Equations, 2002). But Kumily is also a place of spice

trading. Pilgrims to Sabarimala and Mangala Devi temple pass through this town. The

Kottayam – Madurai National Highway (NH 220) pass through Kumily. Apart from

tourism, these factors also make an impact on Kumily. However, since the reserve

194

forest is a protected area, the existing control and protection measures prevent any

change in the land use of the core destination at Thekkady.

Table 4.33: Land use pattern of Kovalam within 500m of CRZ Sl No

Land use pattern Percentage of area

1 Mixed trees with settlement 13.59%2 Reclaimed paddy fields for cultivating banana and tapioca 2.84%3 Agricultural use 27.57%4 Tourism establishments 29.53%5 Quarry 0.00%6 Public and semi-public use 8.91%7 Residential 12.54%8 Stream / water body 1.66%9 Parking and transportation 0.23%10 Dumping yard 0.06%11 Beach 0.02%12 Rock formation 2.06%13 Commercial establishments 0.99% Total 100.00%Source: Committee on Scientific Study of Kovalam, 2002

Motor vehicle traffic is a characteristic of urban area. The residents expressed their

attitude towards the statement, “Traffic problems faced by the residents are due to the

growth of tourism”. The frequency distribution of the opinions of the residents at

Kovalam and Thekkady is given in Table 4.34. It could be seen that majority of the

residents still do not identify tourism as the cause of the traffic problems faced by

them.

Table 4.34: Attitude of residents towards the traffic problems at the destinations Sl No.

Attitude Kovalam Thekkady Frequency Percent Frequency Percent

1 Strongly disagree 21 11.60% 9 6.47%2 Disagree 92 50.83% 85 61.15%3 Do not know 34 18.78% 15 10.79%4 Agree 23 12.71% 25 17.99%5 Strongly agree 11 6.08% 5 3.60% Total 181 100.00% 139 100.00%

195

Employment characteristics from the sample population (Table 4.35) are indicators of

urbanization. Both at Kovalam and Thekkady, only 15 to 16 percent of the working

population is engaged in the Primary Sector. The male working population engaged in

non-agricultural pursuits was 95% and 85% respectively for Kovalam and Thekkady

(Table 3.5). These percentages are against the minimum 75% of the male working

population stipulated by Census of India for considering an area as urban.

Table 4.35: Employment/Occupational division of residents in the sample

Employed sector / Occupation Kovalam Thekkady Total

Number % Number % Number % Employed in Primary sector 97 15.47 92 16.4 189 15.91Employed in Secondary sector 1 0.16 1 0.18 2 0.17Employed in Tertiary sector 156 24.88 122 21.75 278 23.4Housewives 6 0.96 1 0.18 7 0.59Students and children 135 21.53 89 15.86 224 18.86Others 162 25.84 186 33.16 348 29.29Not stated 26 4.15 45 8.02 71 5.98Total 627 100 561 100 1188 100

4.3.6. Commercial land use / Private sector investment 

In Kovalam, the land under tourism use is mostly along the coast and lies between the

Light House beach to Samudra beach. The land near the Light House beach is thickly

built up and the other end in the north is sparsely built up. This sparsely built up land

is owned by KTDC and few others including The Leela (earlier owned by ITDC). The

thickly built up area is under the ownership of local people having small land

holdings.

The resident population in the study area is available for the year 2001 from Census

of India 2001. The growth rate of rural population for the period 1991 – 2001 is

applied for estimating the population beyond 2001. These ratios are estimated in Table

4.36.

196

Both foreign and domestic tourists are considered to arrive at the figure of visitors.

From about five visitors per resident population in the year 2001, the number of

visitors to Kovalam has increased more than four times by 2007. In the case of

Thekkady, the visitor-resident ratio has come down from about 29 visitors per

resident in 2001 to 17 visitors per resident in 2007. By taking the visitors arrived in

the month of January, and average duration of stay at the destinations estimated in the

study by Tata (TCS, 2000) – 4.6 days at Kovalam and 2.5 days at Thekkady – number

of visitors on any day in the month of January is estimated and the visitor-resident

ratio is calculated. The visitor-resident ratio calculated is 1:3 and 1:6 respectively for

Kovalam and Thekkady in any day in the month of January for the year 2007.

Table 4.36: Estimated visitor-resident ratio for the destinations Year Kovalam Thekkady

Res

iden

t po

pula

tion

Vis

itors

(For

eign

an

d do

mes

tic

tour

ists

)

Vis

itor –

R

esid

ent r

atio

(a

nnua

l)

Vis

itor –

R

esid

ent r

atio

(A

day

in Ja

nuar

y)

Res

iden

t po

pula

tion

Vis

itors

(For

eign

an

d do

mes

tic

tour

ists

)

Vis

itor –

R

esid

ent r

atio

(a

nnua

l)

Vis

itor –

R

esid

ent r

atio

(A

day

in Ja

nuar

y)

2001 11305 56653 5.01 0.10 7535 216014 28.67 0.132002 11418 67729 5.93 0.08 7585 195293 25.75 0.172003 11532 112148 9.72 0.16 7636 185366 24.28 0.202004 11647 129809 11.15 0.20 7687 119929 15.60 0.162005 11763 135656 11.53 0.15 7739 134248 17.35 0.152006 11880 185564 15.62 0.23 7791 142373 18.27 0.172007 11998 245269 20.44 0.31 7843 133319 17.00 0.16

4.3.7. Transition from tourism 

Transition from tourism happens when tourism-related activities slow down. Similar

instances that occurred in the past are discussed while reviewing the available

literature. Non-tourism related developments happen and new uses are found with the

existing tourism resources. The present status of the destinations is explained here

197

using GINI index and indirectly, it reveals the shift in the degree of prominence of the

tourism activity.

GINI index is often used as a measure of the inequality in income distribution. Low

values of GINI indices indicate more equitable distribution of income and when the

indices are high, there is more unequal distribution. The index values, expressed in

percentages, are obtained by dividing the area delimited by the Lorenz curve and the

linear curve by the area of the triangle with side length 1. The seasonal concentration

of tourists can be represented using GINI index (Manente & Celotto, 9-11, June

2004). When the index value is high, the seasonal concentration is high, indicating the

risk of decline of the destination. The GINI indices for the years from 1997 to 2007

are computed for Kerala, Kovalam and Thekkady. A quadratic fit in the form y =

a+bx+cx2 is made for the Lorenz curves. The indices calculated are given in Table

4.37.

198

Table 4.37: Seasonal concentration of tourist flows represented using GINI indices

Year Coefficient values (y = a+bx+cx2) Area under

Lorenz curve GINI indexa = b = c =Kerala

1997 1.578913 0.286832 0.006828 0.386790 22.641998 0.552468 0.206867 0.007815 0.369447 26.111999 1.238299 0.324135 0.006427 0.388684 22.262000 -0.641280 0.484026 0.005258 0.410877 17.822001 1.173645 0.194400 0.007791 0.368628 26.272002 -0.065260 0.286079 0.007143 0.380473 23.912003 0.678544 0.315597 0.006689 0.387550 22.492004 0.883459 0.280739 0.007095 0.385708 22.862005 1.119287 0.262527 0.007240 0.383792 23.242006 1.349233 0.267998 0.007097 0.384062 23.192007 1.530048 0.181483 0.007970 0.371695 25.66

Kovalam 1997 2.846334 -0.09977 0.010667 0.334153 33.171998 1.684588 0.273932 0.007023 0.387898 22.421999 0.679915 0.560977 0.004225 0.428127 14.372000 -0.348440 0.422400 0.005862 0.403105 19.382001 1.687498 0.053631 0.009195 0.350192 29.962002 2.045956 0.052124 0.008879 0.342477 31.502003 3.153835 0.042581 0.008926 0.350367 29.932004 1.364170 0.081645 0.008995 0.354305 29.142005 2.046779 0.120522 0.008406 0.360938 27.812006 2.331969 0.103131 0.008552 0.359959 28.012007 2.331141 0.103221 0.008551 0.359969 28.01

Thekkady 1997 2.384326 -0.139990 0.010869 0.316145 36.771998 0.112760 0.140859 0.008530 0.355905 28.821999 0.895552 0.050783 0.009284 0.343808 31.242000 -0.123800 0.171499 0.008386 0.364042 27.192001 2.347311 -0.215450 0.011329 0.293375 41.332002 -0.079130 -0.030600 0.010098 0.320519 35.902003 1.590163 -0.089950 0.010608 0.324524 35.102004 2.517687 -0.429980 0.013912 0.273925 45.222005 1.435666 -0.117680 0.011012 0.322580 35.482006 1.709681 -0.157670 0.011215 0.312095 37.582007 1.708987 -0.157590 0.011214 0.312101 37.58

As such, the indices for Thekkady are relatively higher than that of Kovalam and the

State as a whole, which means the seasonal concentration is high at Thekkady.

Though it cannot be said that the destination is approaching the decline stage, the risk

of decline for Thekkady is higher than that of Kovalam as well as Kerala.

199

4.3.8. Local participation 

The household survey of residents enabled to get the information on the level of

involvement of the residents with tourism. The residents were asked the question:

“How often do you interact with tourists during seasons?” and they were given the

options (a) No interaction, (b) Once in a while, (c) Sometimes, (d) Often and (e)

Almost daily. This gave the following inferences:

• Households with at least one member directly employed in tourism related

services – Answer (e)

• Households with at least one member indirectly employed in tourism related

services – Answers (c) and (d)

• Households with no one employed in tourism related services, but benefitted

from tourism – Answer (b)

• Households that are least benefited from tourism – Answer (a)

The percentage of resident households excluding those who answered (a) is taken as

the local participation rate. Whereas 100% local participation is ideal, the rates

estimated show the level of participation at Kovalam and Thekkady as 41% and 35%

respectively (Table 4.38).

200

Table 4.38: Households benefitted from tourism

Item Kovalam Thekkady

Households

Percent Households

Percent

Households with at least one member directly employed in tourism-related services

28 15.38% 18 12.95%

Households with at least one member indirectly employed in tourism-related services

26 14.29% 22 15.83%

Households with no one employed in tourism-related services, but benefitted from tourism

21 11.54% 9 6.47%

Households that are least benefited from tourism 107 58.79% 90 64.75%

Total 182 100% 139 100% Local participation rate 41.21% 35.25%

4.3.9. Occupancy of tourist accommodation 

The study area in Kovalam has 157 hotels, big and small. These hotels have 958

rooms with 1983 beds (Committee on Scientific Study of Kovalam, 2002, p. 65).

Most of the cheap hotels are along or just behind the beach front. The luxury hotels

are mostly on the northern side.

The first hotel in Thekkady was Aranya Nivas owned by KTDC which was

inaugurated in 1952. In 1955, the first private hotel was established in Kumily – The

Woodlands (Equations, 2002). In 2002, Kumily and the Reserve area had 32 hotels. In

2007, the number of hotels in Kumily was 35 and the number of home stays was 43

according to District Tourism Promotion Council, Idukki.

The survey of accommodation has collected the occupancy rates of hotels over the

years. The occupancy rates are comparatively low in tourist accommodations during

tourist off seasons. The occupancy rates during tourist seasons at Kovalam and

Thekkady are estimated as given in Table 4.39.

201

Table 4.39: Trend of occupancy rates during tourist seasons Year Occupancy rate (%)

Kovalam Thekkady 2007 87.02 77.52 2006 83.87 73.41 2005 81.10 76.02 2004 81.86 74.15 2003 81.63 70.68 2002 81.16 76.41 2001 81.38 72.28

More and more tourist beds were provided with the establishment of new tourist

accommodations in the form of hotels and home stays. Since capacity of

accommodations always exceeded the tourist arrivals, occupancy of hotels was never

a limiting factor to arrest the growth of tourism in the destinations.

4.3.10. Historicity 

“Tourism is a major mission and has tremendous potential for growth in this beautiful

territory. Kerala has many tourism and pilgrim centers such as Sabarimala,

Guruvayoor, Bolghatty Palace, Kumarakom Lake resort near Kottayam, beaches like

Kovalam, hill stations like Munnar and wild life sanctuaries like Eravikulam and

Periyar, architectural and civilizational heritage. Kerala is one of the rare places where

tropical forests, vast beautiful coast lines, mountains, water bodies, lakes, beautiful

sunshine etc. coexist. It is nature’s special manifestation” (Kalam, 2005). Nature is the

backbone of tourism in Kerala and tourism in Kerala evolved years back and thrives

on its rich natural resources.

Kovalam has been internationally renowned beach resort since 1930 (Committee on

Scientific Study of Kovalam, 2002). The late Maharaja of Travancore Shree Chithira

Thirunal Balaramavarma built the Halcyon Castle at Kovalam and made it a summer

retreat. Travancore Public Works Department maintained two bath rooms, two

202

changing rooms and a well near the coast in the early 1940s. In 1959, ‘Club

Mediterranee”, a French organization, attempted to make Kovalam a beach resort and

foreign tourists in small numbers started visiting Kovalam (KITTS, 2005). In 1966,

Indian Tourism Development Corporation (ITDC), Government of India, built the

five star hotel Ashoka. “Kovalam Grove”, a beach resort of ITDC was inaugurated in

1972. The Kovalam – Vizhinjam development authority was set up in 1975 for the

development of the region. In 1981, Kerala Tourism Development Corporation

(KTDC) started Hotel Samudra. Private initiatives started in the 1980s. Chartered

flights started coming to Kovalam by 1995.

Historically, Thekkady was part of Travancore and was under the reign of Travancore

Rajas. In 1886, laborers from different parts of Tamil Nadu and Travancore – Cochin

region began to settle in Thekkady area during the construction of the Mullaperiyar

dam. The artificial lake formed by the construction of Mullaperiyar Dam, attracted

wild life and later people to view wild life (Equations, 2002). In 1935, Nellikkapetty,

in which Thekkady was a part, was declared as Project Tiger Reserve. In 1956, the

region was declared as Periyar Wildlife Sanctuary. Boating in the lake to view wild

life is one of the main tourism activities. The tourism potential of Thekkady and the

different plantations in the region (National Transportation Planning and Research

Centre, 2004) were catalytic in the development of hotels and tourism related

facilities and the development of Kumily Town (National Transportation Planning

and Research Centre, 2004). The Kerala Tourism Development Corporation (KTDC)

is the only tourism service provider inside the Periyar Tiger Reserve with

accommodation, restaurant and boating facilities. Aranya Nivas was its first hotel,

which was named and inaugurated by Pandit Jawaharlal Nehru in 1952 (Equations,

2002). Two other hotels owned by KTDC are Periyar House and Lake Palace.

203

As Lundtrop and Wanhill points out in their study, the number of people who knows

about a destination Mt at time t, approaches the total population M in the target

market, when the knowledge about the destination spreads (Lundtrop & Wanhill,

2001). Thus as a destination becomes more and more popular, the need for

advertisements to familiarize the destination comes down. The source of information

to tourists shifts from advertisement or publicity materials to ‘word of mouth’. The

opinion survey conducted among tourists also extracted information on the sources of

information the tourists had before taking the decision to visit the destination.

Distribution of tourists on the basis of sources of information they had about the

destination is given in Table 4.40. The table is compiled only for the first time visitors

to the respective destinations.

Table 4.40: Sources of information for the first time visitors to Kovalam and Thekkady Sl No

Source of information Kovalam Thekkady Number of tourists

Percentage Number of tourists

Percentage

1 Advertisements 45 6.21% 19 5.79%2 Published articles 90 12.41% 23 7.01%3 Friends/relatives 208 28.69% 66 20.12%4 Tourist Offices 15 2.07% 1 0.30%5 Internet 146 20.14% 77 23.48%6 Tour operator 177 24.41% 72 21.95%7 Lonely Planet/Tourist guides 29 4.00% 37 11.28%8 Others 15 2.07% 33 10.06% Total 725 100.00% 328 100.00%Note: Includes multiple choice stated by the tourists

When the source of information is “friends & relatives”, it can also be seen as a

recommendation to visit the site. This reflects the popularity of the site on one side

reflecting the historicity and indirect promise of satisfaction / experience that can be

desired from visiting the destination. As a measure of historicity, a high share of

tourists with the sources of information as “friends & relatives” would mean a

destination in the growth or mature stage of the life cycle.

204

4.3.11. Tourism promotion 

A measure of tourism promotion specifically for the selected destinations, though as a

factor influencing the product life cycle, is not available and at the same time difficult

to comprehend. The promotion efforts of Government of Kerala are meant for

promoting the product classes. The Government uses print media and television

advertisements and also participates in road shows and tourism fairs. In 2007-08, Rs.

4.5 crores was spent for promoting domestic tourism and Rs. 6.5 crores was spent for

promoting international tourism (Table 4.41). Tourism promotion expenses for the

destinations are estimated using the average promotion expenses for foreign tourists

available for the years from 2004-05 to 2007-08. The estimated figures are given in

Table 4.42.

Though the average promotion expense per tourist is declining, the promotional

expenses have shown a growing trend. This characteristic is typical for a product in

the growth stage. Percentage of promotion expense to the earnings is taken as the

measure of the factor studied here. The estimated percent of promotional expenses for

Kovalam and Thekkady are given in Table 4.43.

205

Table 4.41: Advertising spent in Kerala tourism (Rupees in lakhs)

Year Print Television Road shows & Trade

Fairs National International National International National International

2004 – 05 150 173 22 160 25 75 2005 – 06 150 195 150 170 65 100 2006 – 07 262 150 100 165 150 2007 – 08 200 200 150 250 100 200 Source: Department of Tourism, Government of Kerala

Table 4.42: Estimated tourism promotion expense of Kovalam and Thekkady

Year

Average expense per

foreign tourist (Rs)

Kovalam Thekkady Number

of foreign tourists

Estimated expense

(Rs. lakhs)

Growth rate (%)

Number of

foreign tourists

Estimated expense

(Rs. lakhs)

Growth rate (%)

2004-05 118 46074 54.37 28884 34.08 2005-06 134 56268 75.40 38.68 27061 36.26 6.392006-07 109 78998 86.11 14.20 31930 34.80 -4.022007-08 126 120663 152.04 76.56 30038 37.85 8.75 Table 4.43: Percentage of promotional spent for Kovalam and Thekkady

Year Percent of promotional expense

Kovalam Thekkady 2004-05 1.03% 1.89% 2005-06 0.96% 1.76% 2006-07 0.75% 1.38% 2007-08 0.79% 1.45%