chapter iv profile of entrepreneurs and their...

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CHAPTER IV

PROFILE OF ENTREPRENEURS AND

THEIR BUSINESS PERFORMANCE

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Profile of Entrepreneurs and their Business Performance

Demographic Profile of the Entrepreneurs

Comprehensive study of the various demographical factors of the

entrepreneurs such as age, gender, place of origin and qualification was made

by finding out cross relationship between the variables. The cross tab procedure

was applied by the application of SPSS software. The results are tabulated and

the corresponding interpretations are presented in the following pages.

TABLE 4.1

GENDER AND AGE OF THE RESPONDENTS

Present age groups of the entrepreneurs Gender

20-30 31-40 41-50 51-60 Total

Male 15 (10.0%) 35 (23.3%) 43 (28.7%) 57 (38.0%) 150 (100.0%)

Female 12 (24.0%) 21 (42.0%) 15 (30.0%) 2 (4.0%) 50 (100.0%)

Total 27 (13.5%) 56 (28.0% 58 (29.0%) 59 (29.5%) 200 (100.0%)

Source: Primary data.

As could be seen in Table 4.1, male and female ratio is 3:1. Male

members dominate in all the age groups. Interestingly two-thirds of the male

respondents are in the age group of 40-50, whereas the same proportions of

women entrepreneurs are found in the younger age, i.e. in 20s or 30s. It may be

inferred from the data that male entrepreneurs entered business at a younger

age and they have been around in business for quite some time. In contrast,

female entrepreneurs were almost negligible in the higher age group with just

4%. It could be due to the fact that female literacy and their entry into

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organized activity, more particularly entering business arena is a recent

phenomenon. The various women empowerment progress and incentives and

specialized schemes would have prompted women to seek an entrepreneurial

career, which is more pronounced in the last few years. Hence a substantial

number of women respondents are found in the age groups of 20–30 and 31-40.

TABLE 4.2

AGE AND EDUCATION OF THE RESPONDENTS

Age Qualification

20-30 31-40 41-50 51-60 Total

Non-School 7

(87.5%) 0

(`.0%) 1

(12.5%) 0

(.0%) 8

(100.0%)

High School Pass/Pre-university

10 (50.0%)

5 (25.0%)

4 (20.0%)

1 (5.0%)

20 (100.0%)

Graduation/Post Graduation/Professional

10 (5.8%)

51 (29.7%)

53 (30.8%)

58 (33.7%)

172 (100.0%)

Total 27

(13.5%) 56

(28.0%) 58

(29.0%) 59

(29.5%) 200

(100.0%)

Source: Primary Data.

An attempt was also made to check the relationship between the

qualification and age of the respondents. Table 4.2 shows, that 172 out of 200

respondents (86%) studied up to graduation and above. Thus, a very high

proportion of educated entrepreneurs are operating in Bangalore. It may be

seen that an overwhelming majority of the respondents had higher education,

thus it is evident that entrepreneurs with good academic credentials and training

chose to enter business. Though entrepreneurial history all over the world

shows that many entrepreneurs have made a mark in business without higher

education, it is found of late, people with good education and training are

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entering business. They possess undergraduate, post graduate and professional

qualifications.

TABLE 4.3

PLACE OF ORIGIN AND AGE GROUPS Age groups of entrepreneurs

Origin 20-30 31-40 41-50 51-60 Total

Local Kanadiga 16

(34.0%) 12

(25.5%) 8

(17.0%) 11

(23.4%) 47

(100.0%)

Local Non-Kanadiga 6

(6.3%) 30

(31.3%) 31

(32.3%) 29

(30.2%) 96

(100.0%)

NRI Kanadiga 0

(.0%) 4

(19.0%) 10

(47.6%) 7

(33.3%) 21

(100.0%)

NRI Non Kanadiga 2

(7.4%) 7

(25.9%) 7

(25.9%) 11

(40.7%) 27

(100.0%)

Foreign Nationals 3

(33.3%) 3

(33.3%) 2

(2.2%) 1

(11.1%) 9

(100.0%)

Total 27

(13.5%) 56

(28.0%) 58

(29.0%) 59

(29.5%) 200

(100.0%)


The relationship between place of origin and age as presented in Table

4.3, shows that bulk of the entrepreneurs are young. About 66.6% of them fall

in the age group of 20-30 and 31-40. The local non Kanadiga people are

maximum (48.0%) in number and are almost double the number than that of

the local Kandigas (23.5%). It was found people from all the states of India

found excellent business opportunities in Bangalore. Added to that, there were

the incentives and subsidies offered by the government of Karnataka and the

accommodative spirit of the local population. The positive attitude and warmth

that the local people are known for, attracted many non Kanadigas to flock to

Bangalore and try their luck in business. Thus, the post liberalization period

since early 90s witnessed the establishment of a large number of business

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ventures. The other interesting fact is the presence of the foreign entrepreneurs

in Bangalore. Though the number of foreign entrepreneurs, (9 members out of

200), is a small number, it proves the point that tourism as a business lures

foreign entrepreneurs also. Personal interviews revealed that these people were

mostly in providing software solutions to tourism units and came under the

purview of ‘vendors to tourism’. Similarly, the presence of the NRI

entrepreneurs (48 out of 200), shows that about one-fourth of the respondents

have some foreign connections. We understand tourism requires a high level of

international networking and these NRI back ground people have a natural

advantage in providing the global touch.

TABLE 4.4

GENDER AND PLACE OF ORIGIN

Entrepreneurs’ place of origin

Gender Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total

Male 41 (27.3%)

71 (47.3%)

17 (11.3%)

18 (12.0%)

3 (2.0%)

150 (100.0%)

Female

6 (12.0%)

25 (50.0%)

4 (8.0%)

9 (18.0%)

6 (12.0%)

50 (100.0%)

Total 47 (23.5%)

96 (48.0%)

21 (10.5%)

27 (13.5%)

9 (4.5%)

200 (100.0%)


The study of gender with place of origin as presented in Table 4.4 shows

that among male members 47.3% were local non Kanadiga and 18% NRI non

Kanadiga members, showing 65.3% of the male entrepreneurs were from

outside the state. Among the female respondents, 50.0% were local non-

Kanadiga and another 18.0% non Kanadiga NRI (totaling 68%). The trend

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clearly shows that in both the male and female entrepreneur categories, the

immigrants constitute a substantial portion.

TABLE 4.5

GENDER AND EDUCATION

Qualification

Gender Non-

School High School Pass / Pre-university

Graduation / Post Graduation/

Professional

Total

Male 7 (4.7%) 14 (9.3%) 129 (86.0%) 150 (100.0%)

Female 1 (2.0%) 6 (12.0%) 43 (86.0%) 50 (100.0%)

Total 8 (4.0%) 20 (10.0%) 172 (86.0%) 200 100.0%)


The relationship test between respondents’ gender and educational

qualification as per Table 4.5 shows a high level of qualification for both male

and female - together constituting 86.0% having graduation/professional/post-

graduation achievements. Other significant finding is that there are 7 men and 1

woman (total 8) entrepreneurs who did not have any formal education even up

to school level, but still made it in tourism business.

Age of Entrepreneurs and Delivery of Quality Service

An attempt was made to find out the association of age of the

entrepreneurs and delivery of quality service through testing the following

hypothesis:

Ho: No significant association is established between the age of the

respondents and entrepreneurial business performances in terms of

delivering quality tourism and allied services.

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This hypothesis has two components as one predictor (independent) and

the other is dependent, as the age would be the independent variable. The

dependent variable consists of different aspects of the quality venture

performance. They relate to size of the business, motivation of the

entrepreneur, growth of the venture, competition, branding, venture break-even

time and venture life-span. Each of these variables is tested with the

independent variable ‘age of the entrepreneur’. Cross tab and Pearson Chi–

Square test have been applied separately for each combination. All the

individual dependent variables’ association results are consolidated to the

combined dependent variable ‘quality venture performance’.

TABLE 4.6

TYPE OF BUSINESS AND AGE

Age groups of the entrepreneurs Pearson

Chi-square Category of

Tourism Business

20-30 31-40 41-50 51-60 Total

Hotels 3

(12.0%) 5

(20.0%) 7

(28.0%) 10

(40.0%) 25

(100.0%)

Restaurants 13

(56.5%) 7

(30.4%) 2

(8.7%) 1

(4.3%) 23

(100.0%)

Travel Agencies/ Tour Operators

2 (3.4%)

16 (27.1%)

25 (42.4%)

16 (27.1%)

59 (100.0%)

Transport Operator

4 (18.2%)

4 (18.2%)

6 (27.3%)

8 (36.4%)

22 (100.0%)

Tourism Business Vendors

1 (2.9%)

12 (34.3%)

6 (17.1%)

16 (45.7%)

35 (100.0%)

Entertainment Service Providers

4 (11.1%)

12 (33.3%)

12 (33.3%)

8 (22.2%)

36 (100.0%)

Total 27

(13.5%) 56

(28.0%) 58

(29.0%) 59

(29.5%) 200

(100.0%)

60.708

.000


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The study of the relationship between the type of business and their the

respondents age as presented in Table 4.6 reveals that entrepreneurs operating

hotels are mostly older; those operating restaurants are relatively younger;

travel agents / tour operators fall mostly in the middle aged group; transport

operators are uniformly distributed over all the age groups; while entertainment

service providers are middle aged. The study also reveals the age groups of 31-

40, 41-50 and 51-60 are equally distinguished in all the business categories. It

is also evident that restaurant business mostly draw younger people whereas

hotels, travel agencies and entertainment providers tend to be middle-age and

above. Thus, there is a strong association between the various categories of

tourism ventures and the age of the entrepreneurs. Pearson Chi-square test

show a significance value of .000, showing the null hypothesis is rejected. This

confirms the fact there is effective association between categories of business

and the age of the entrepreneur.

TABLE 4.7

RESPONDENTS AGE AND SIZE OF BUSINESS

Age of the Respondents

Pearson Chi-

Square

Size of Business

20-30 31-40 41-50 51-60 Total

Small Scale 26

(26.0%) 32

(32.0%) 24

(24.0%) 18

(18.0%) 100

(100.0%)

Medium Scale

1 (1.3%)

22 (27.8%)

26 (32.9%)

30 (38.0%)

79

(100.0%)

Large Scale 0

(.0%) 2

(9.5%) 8

(38.1%) 11

(52.4%) 21

(100.0%)

Total 27

(13.5%) 56

(28.0%) 58

(29.0%) 59

(29.5%) 200

(100.0%)

38.311 .000


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The study of business size and age is shown in Table 4.7. It could be

seen that maximum units were small scale (50%) followed by were medium

(39.5%) and large scale 10.5%. Most of the tourism units tended to be small

and medium in nature. The small scale units are run by young and middle aged

people; the medium scale units are owned by middle and elderly people and the

large scale units are operated by the elderly. Classification of the size of the

firm has been done according to Govt. of India grading of industries as: Units

with total assets < 1 crore – small scale; > 1crore < 10crores – medium scale; >

10 crores – large scale. Thus we can see managing assets worth 10 crores and

above require the experienced professionals with good exposure to business.

There were many respondents who worked in reputed tourism organizations,

achieved their expertise and then quit their jobs to start their ventures. Thus a

number of interesting relationships exist between the size of the venture and the

age of the entrepreneurs. The Pearson Chi–Square test produces a value of

significance of .000, proving the null hypothesis is rejected. This further

confirms that size of the venture has association with age of the entrepreneurs.

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TABLE 4.8

MOTIVATION TO START VENTURE AND

THE AGE OF THE RESPONDENTS

Age groups of the entrepreneurs Chi-Square

Motivation to Start

Entrepreneurship 20-30 31-40 41-50 51-60 Total

Urge to Achieve 20

(17.9%) 32

(28.6%) 28

(25.0%) 32

(28.6%)

112

(100.0%)

Excess Funds 1

(5.6%) 7

(38.9%) 6

(33.3%) 4

(22.2%) 18

(100.0%)

Professional Expertise

0 (.0%)

12 (27.9%)

14 (32.6%)

17 (39.5%)

43 (100.0%)

To Capitalize Demand

0 .0%

2 33.3%

2 33.3%

2 33.3%

6 100.0%

Family Business Support

6 (28.6%)

3 (14.3%)

8 (38.1%)

4 (19.0%)

21 (100.0%)

Total 27

(13.5%) 56

(28.0%) 58

(29.0%) 59

(29.5%) 200

(100.0%)

19.003 .008


Motivation to start venture and the age of the respondents as

demonstrated by Table 4.8 revealed ‘The urge to achieve’ was the single

motivational force found common across all age groups. This proves the

achievement motivation is strong for entrepreneurs of all age groups and it

supersedes all other choices. ‘Professional expertise’ does not have any score in

the 20-30 years age group and in other three age groups the response increases

progressively with the age groups. This is understandable as the younger

entrepreneurs do not have work experience. Thus the eldest group shows

maximum affinity for professional expertise. Thus there is relationship between

motivation to start entrepreneurship and the age of the entrepreneurs. This fact

is further confirmed by the chi–square test significance value of .008 that

suggests the null hypotheses should be rejected. There is considerable amount

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of association between motivation to start business and age of the

entrepreneurs.

TABLE 4.9

VENTURE GROWTH AND AGE OF RESPONDENTS

Age Chi-

Square Progress

in the Business 20-30 31-40 41-50 51-60 Total

Loss Making 4 (36.4%) 5 (45.5%) 0 (.0%) 2 (18.2%) 11 (100.0%)

Break Even 7 (25.0%) 7 (25.0%) 10 (35.7%) 4 (14.3%) 28 (100.0%)

Moderate Profits 11 (10.5%) 33 (31.4%) 27 (25.7%) 34 (32.4%) 105 (100.0%)

High Profits 5 (8.9%) 11 (19.6%) 21 (37.5%) 19 (33.9%) 56 (100.0%)

Total 27 (13.5%) 56 (28.0%) 58 (29.0%) 59 (29.5%) 200 (100.0%)

.048 21.160


Relationship of business growth with the age of the respondents study

as projected by Table 4.9 reveals out of the 11 failure cases 4 are from 20-30

age group and 5 are from 31-40 age group. These shows the younger

respondents lack the tenacity to face bad times. This is due to the intense

competition in the tourism business and the high level of service delivery skills

required which may not be present in the 20-30 groups. The best profit making

track belong to 31-40 and 41-50 groups and the failure rate is also the least in

these categories. This finding confirms the fact that one needs to possess

considerable tourism service operational skills to run their ventures. The results

thus show there is association between growth of business and age of the

entrepreneurs. The significance value of the chi-square test of .048 suggests the

null hypothesis is rejected.

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TABLE 4.10

COMPETITION AND AGE OF RESPONDENTS

Age

Competition 20-30 31-40 41-50 51-60

Total

Yes 21 (13.0%) 42 (26.1%) 48 (29.8%) 50 (31.1%) 161 (100%)

No 6 (15.4%) 14 (35.9%) 10 (25.6%) 9 (23.1%) 39 (100%)

Total 27 (13.5%) 56 (28.0%) 58 (29.0%) 59 (29.5%) 200 (100%)


As per Table 4.10, it is seen that respondents across all the age groups

agree that they faced strong competition. There is almost an unanimous view

that strong competition exists. It could also be due to the fact that respondents

who are 40s and 50s in age are more conscious of the existing competition in

their respective businesses. On the other hand, the younger entrepreneurs’ less

acknowledgement of competition shows that they are either less experienced to

assess the impact of competition or are more courageous to take on the

competition.

TABLE 4.11

BRAND BUILDING EFFORTS OF THE RESPONDENTS Age

Brand Building 20-30 31-40 41-50 51-60

Total

Yes 16 (11.7%) 37 (27.0%) 38 (27.7%) 46 (33.6%) 137 (100%)

No 11 (17.5%) 19 (30.2%) 20 (31.7%) 13 (20.6%) 63 (100%)

Total 27 (13.5%) 56 (28.0%) 58 (29.0%) 59 (29.5%) 200 (100%)


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Study of brand building with age as per Table 4.11, shows an interesting

picture in the ‘yes’ category. The number of responses increasing

proportionately with the individual age groups. This shows, as the age of the

entrepreneurs advances the capacity and urge to build brand also increases.

Brand building requires deep knowledge of the market and years of brand

management experience that can be expected in senior people. The respondents

were found busy in activities as selective advertising, developing of logo and

brand slogan, direct marketing, product positioning and publicity – all aimed to

strengthen their brand image. That is the reason 51-60 years age group has the

maximum number of respondents who built a brand of their own in business.

TABLE 4.12

RESPONDENTS’ AGE AND BUSINESS BREAK-EVEN PERIOD Age Break

Even time 20-30 31-40 41-50 51-60 Total

Chi-Square

Within One Year

17 (26.6%) 25 (39.1%) 16 (25.0%) 6 (9.4%) 64 (100%)

2-5 Years 9 (8.3%) 25 (23.1%) 36 (33.3%) 38 (35.2%) 108 (100%)

6-10 Years 1 (3.6%) 6 (21.4%) 6 (21.4%) 15 (53.6%) 28 (100%)

Total 27 (13.5%) 56 (28.0%) 58 (29.0%) 59 (29.5%) 200 (100%)

33.482 .000


Break-even of business as presented in table 4.12 shows that in the case

of 108 respondents, their businesses had broke even in the first 2-5 years of

operation. Again, interestingly all these units broke-even in 2-5 years are

owned by respondents who are in their 40s and above. Whereas in the within

one year’, category it can be seen the concentration is more towards the young

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groups of 20-30 and 31-40. This shows that the young entrepreneurs tend to

break even within one year. It could be largely due to the fact that younger

respondents own business in the niche area of tourism and are relatively small

in size. There are certain associations among the age and break-even time of

the ventures. The chi–square significance value also shows .000, indicating the

null hypotheses that the variables are not related, should be rejected.

TABLE 4.13

AGE OF THE RESPONDENTS AND VENTURE LIFE SPAN

Age Venture Life Span

20-30 31-40 41-50 51-60 Total

Pearson Chi-

Square

One Year 20 (50.0%) 14 35.0%) 4 (10.0%) 2 (5.0%) 40 (100%)

2-4 Years 6 (7.1%) 37 (43.5%) 29 (34.1%) 13 (15.3%) 85 (100%)

5-10 years 1 (1.3%) 5 (6.7%) 25 (33.3%) 44 (58.7%) 75 (100%)

Total 27 (13.5%) 56 (28.0%) 58 (29.0%) 59 (29.5%) 200 (100%)

112.336 .000


Venture life span and age of entrepreneurs’ as shown in Table 4.13,

reveals that 85 ventures aged 2-4 years are owned by respondents in the age

group of 31-40 years, followed by 37 owned by respondents in the age group of

41-50 years. However in the next highest category with response of 75 the

concentration is on 41-50 years group with 25 and 51-60 years group with

score of 44. This show the elderly people are more visible in ventures that

exhibited longer life span. In contrast The chi–square test produces a

significance value of .000 that suggests the null hypothesis is reject, the units

owned by younger respondents are relatively young and mostly start-up units.

There are clear associations between venture life span and age of the

entrepreneurs.

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The above mentioned eight aspects of business as: category of business,

size of the business, venture motivation, venture growth, competition,

branding, venture break-even time and venture life-span all have been analyzed

quantitatively as well as qualitatively to test whether there exists any

association between these variables and the age of the entrepreneur. Result

show there are relationships between each variable and age of the entrepreneur.

Thus all the business aspects put together will constitute ‘Entrepreneurial

business performances in terms of delivering quality tourism and allied

services’; that in turn is also significantly associated with the age of the

entrepreneurs. So age of the entrepreneurs does have significant association

with business performance. The following null hypothesis is therefore rejected.

Ho: No significant association is established between the age of the

respondents and the business performance in terms of delivering

quality tourism and allied services

Gender vis-a-vis Tourism Enterprises

In an attempt to find out the role of the gender of the respondents and its

association with venture opportunities and challenges, it was decided to

examine the following hypothesis.

Ho: The gender of the respondents is in no way associated with the

tourism and allied entrepreneurial business opportunities and

challenges:

The independent variable gender with the group of dependent variables

that sum up the combined dependent variable business opportunities and

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challenges, were analysed using cross tabs and chi-square test. The dependent

variables are categories of business, size of business, motivation, venture

progress, competition, branding, break-even time, and venture life span. Each

one of this dependent variable was tested with the independent variable gender.

Cross tabs and Chi–Square test was applied using SPSS. The results and

interpretations are presented in the following pages.

TABLE 4.14

ENTREPRENEURS GENDER AND TYPES OF BUSINESS

Categories of Tourism Business

Hotels Restaurants Travel Agencies/

Tour Operators

Transport Operator


Entertain--ment

Service Providers

Total Chi Square

Male 22

(14.7%) 16

(10.7%) 48

(32.0%) 20

(13.3%) 27

(18.0%) 17

(11.3%) 150

(100.0%)

Female 3

(6.0%) 7

(14.0%) 11

(22.0%) 2

(4.0%) 8

(16.0%) 19

(38.0%) 50

(100.0%)

Total 25

(12.5%) 23

(11.5%) 59

(29.5%) 22

(11.0%) 35

(17.5%) 36

(18.0%) 200

(100.0%)

21.757 .001


In the study to establish relationship between gender and categories of

business, it was found as shown in Table 4.14, the maximum number of the

male and female respondents were in the travel agencies/tour operation

business. It may be noted that hotels and restaurants were dominated by the

male respondents. Vendors of tourism and entertainment business also had

more male members. The women respondents are found in good number in the

entertainment business provider. The total male to female entrepreneurs’ ratio

was 3:1. Thus male members clearly outnumbered the women in all the

categories of business. The Chi-square test produced a result of .001, denoting

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the null hypotheses can be rejected; thereby confirming the associations

between the gender of the entrepreneurs and the type of business.

TABLE 4.15

RESPONDENTS’ GENDER AND SIZE OF BUSINESS

Size of Business Organization Chi Square Gender

Small Scale Medium Scale Large Scale Total

Male 75 (50.0%) 57 (38.0%) 18 (12.0%) 150 (100.0%)

Female 25 (50.0%) 22 (44.0%) 3 (6.0%) 50 (100.0%)

Total 100 (50.0%) 79 (39.5%) 21 (10.5%) 200 (100.0%)

1.627 .443


The gender and size of business results presented in Table 4.15 shows a

fairly uniform distribution. Male and female respondents constitute the same

proportion between small, medium and large enterprises. It appears that gender

does not influence the size of the units. Both male and female respondents are

found to have set up establishments of different sizes in Bangalore. The Chi-

square test of significance show score of .443 suggesting the null hypotheses is

not rejected. Thus, it is accepted that size of the unit is not gender dependent.

TABLE 4.16

GENDER AND MOTIVATION TO ENTER BUSINESS

Gender of the entrepreneurs Chi-Square Motivation to Start Entrepreneurship Male Female Total

Urge to Achieve 78 (69.6%) 34 (30.4%) 112 (100.0%)

Excess Funds 13 (72.2%) 5 (27.8%) 18 (100.0%)

Professional Expertise 35 (81.4%) 8 (18.6%) 43 (100.0%)

To Capitalize Demand 5 (83.3%) 1 (16.7%) 6 (100.0%)

Family Business Support 19 (90.5%) 2 (9.5%) 21 (100.0%)

Total 150 (75.0%) 50 (25.0%) 200 (100.0%)

5.631 .228


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As could be seen in Table 4.16, the highest numbers of female

respondents motivated by ‘urge to achieve’ were in the ratio of 2:1 with the

male respondents in this category. Notable factor is that eight members out of

50 women respondents were driven by ‘professional expertise’. It indicates

that many women entrepreneurs had much less work experience or technical

expertise to utilize in their ventures compared to male respondents. The

Chi–square test shows the score .228 suggesting the null hypothesis is not

rejected. Thus, it is concluded that motivation to start a business unit is not

gender dependent.

TABLE 4.17

VENTURE GROWTH AND RESPONDENTS GENDER

Gender of entrepreneurs Venture Growth

Male Female Total

Chi-Square

Loss Making Unit 9 (81.8%) 2 (18.2%) 11 (100.0%)

Break Even 22 (78.6%) 6 (21.4%) 28 (100.0%)

Moderate Profits 79 (75.2%) 26 (24.8%) 105 (100.0%)

High Profits 40 (71.4%) 16 (28.6%) 56 (100.0%)

Total 150 (75.0%) 50 (25.0%) 200 (100.0%)

.847

.838

Venture growth and gender as shown in Table 4.17 reveal the units’

growth as measured by profit making potential of the business. Slightly more

than half (105 out of 200) of the units are making moderate profits while 28%

of the units (56 out of 200) are making high profits. Further, the percentage of

high profit ventures between male and female respondents shows that many

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units owned by female respondents are making profits compared to the ones

owned by male respondents. However, the results show there are proportionate

distribution of male and female respondents in all the three categories as ‘loss

making’, break-even’, ‘moderate profits’ and ‘high profits’ categories.

Difference in gender does not have significant association in business growth.

The chi-square test result shows significance value of .838 indicating the null

hypothesis is not rejected.

TABLE 4.18

PERCEPTION OF COMPETITION AND

GENDER OF RESPONDENTS

Gender Strong Competition

Male Female Total

Yes 125 (77.6%) 36 (22.4%) 161 (100.0%)

No 25 (64.1%) 14 (35.9%) 39 (100.0%)

Total 150 (75.0%) 50 (25.0%) 200 (100.0%)


As regards the perception of competition between male and female

respondents, on the whole, both the categories are fully aware of the intensity

of competition in their respective business, though the percentage of female

respondents who do not perceive the competition as presented in Table 4.18, is

slightly higher compared to male respondents (28% and 16.7% respectively). It

shows a large number of respondents got into niche business where the

competition is not severe.

162

TABLE 4.19

GENDER AND BRAND BUILDING EXERCISE

Gender Brand Building

Male Female Total

Yes 99 (72.3%) 38 (27.7%) 137 (100.0%)

No 51 (81.0%) 12 (19.0%) 63 (100.0%)

Total 150 (75.0%) 50 (25.0%) 200 (100.0%)

Source: Primary data. The relationship between brand building and gender of the respondents

in Table 4.19 reveal out of 200 sample respondents, 137 respondents are keen

in brand building. Among this 99 respondents were male and 38 respondents

were female. The result shows that the male respondents were almost three

times that of female respondents. This shows women respondents were more

actively engaged in brand building. Business details of some of these women

respondents have been mentioned in the subsequent part of this chapter.

TABLE 4.20

VENTURE BREAK-EVEN PERIOD AND GENDER

Gender Break Even Period

Male Female Total Chi-Square

Within One Year 41 (64.1%) 23 (35.9%) 64 (100.0%)

2-5 Years 84 (77.8%) 24 (22.2%) 108 (100.0%)

6-10 Years 25 (89.3%) 3 (10.7%) 28 (100.0%)

Total 150 (75.0%) 50 (25.0%) 200 (100.0%)

7.575 .023


163

The break-even period and gender matrix as shown in Table 4.20 reveal

that the maximum numbers of 108 respondents were in 2-5 years group. In this

group the male to female ratio were 4:1.Totally 64 respondents broke even

within 1 year and the male is to female ratio was 2:1. This show the majority of

the entrepreneurs (totally 172) could break even within 5 years. Bangalore

tourism entrepreneurs had the fortune of early break-even period. Out of the

total 50 female respondents, 48 of them could break-even in the first 5 years.

This also indicated most of the establishments were small to medium with less

capital requirement and high return on investment. The chi-square test gives a

value of .023, showing the null hypothesis is rejected. It can be concluded that

break-even period has association with the gender.

TABLE 4.21

VENTURE LIFE SPAN AND RESPONDENTS GENDER

Gender Venture Life Span

Male Female Total

One Year 25 (62.5%) 15 (37.5%) 40 (100.0%)

2- 4 Years 59 (69.4%) 26 (30.6%) 85 (100.0%)

5-10 years 66 (88.0%) 9 (12.0%) 75 (100.0%)

Total 150 (75.0%) 50 (25.0%) 200 (100.0%)


Table 4.21 shows that the maximum number of respondents in the

category of the venture life span and gender study falls in 2-4 years bracket

with 85 as the score. Here male to female ratio works out to 2:1. Next in line

comes 5-10 years category with the total response score of 75; the male to

female ratio stand as 7:1. Clearly the male members are more in number in

164

ventures with longer life span. The one year category shows the male to female

ratio as 3:2. That is the female representation is clearly high in the businesses

that require less life span.

In the case of gender and its association with the different aspects of

business as: categories of business, size of business, motivation, venture

growth, competition, branding, break-even time, and venture life span, it may

seen that there are associations with the gender in deciding entrepreneurial

progress. At the same time, there are few occasions (three cases) where the chi-

square significance value did not reject the null hypothesis of the individual

aspect. Thus we can conclude by saying that gender has less influence on the

course of entrepreneurial business. Members of both sexes tend to have similar

influence on the business and its success and their differences do not bring any

major change. Age comparatively has much more influence in deciding the

destiny of the entrepreneurial business.

Ho: Gender of the entrepreneurs is no way associated with the tourism

business opportunities and challenges

The above mentioned null hypothesis however is rejected.

Respondents place of origin and venture success

In order to assess the relationship between the place of origin and

business success the following null hypotheses was introduced.

HO: There is no significant association between the place of origin of the

entrepreneurs and the factors determining success in the tourism

ventures.

165

The independent variable ‘place of origin of entrepreneur’ was used to

find out cross relationship with a number of dependent variables that add up to

‘entrepreneurial venture success.’ These variables were: type of business,

organizational structure, motivation, innovations, venture growth, competition,

brand building, break-even period and venture life span.

The independent variable place of origin has been tested with each of

the above mentioned variables applying crosstabs and chi-square test using

SPSS. The results and interpretations are presented in the following pages.

TABLE 4.22

RESPONDENTS SIZE OF BUSINESS AND THEIR PLACE OF ORIGIN

Entrepreneurs Place of Origin

Size of Business

Organization

Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total Chi-Square

Small Scale 30

(30.0%) 41

(41.0%) 10

(10.0%) 13

(13.0%) 6

(6.0%) 100

(100.0%)

Medium Scale 16

(20.3%) 44

(55.7%) 10

(12.7%) 6

(7.6%) 3

(3.8%) 79

(100.0%)

Large Scale 1

(4.8%) 11

(52.4%) 1

(4.8%) 8

(38.1%) 0

(.0%) 21

(100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

21.403 .006


The study of size of business and origin of domicile as presented in

Table 4.22 reveals that the non Kanadiga (local & NRI) respondents were

found operating large ventures (19 out of 21). The Kanadiga (local & NRI)

respondents were found largely in small ventures. There were 6 foreigners in

the small scale and 3 foreigners in the medium scale units. Further in regard to

domicile status, migrant to local ratio was 2:1. Thus, there is an association

166

between venture size and entrepreneurs place of origin. The chi-square test

shows a significance score of .006; suggesting that the null hypothesis is

rejected. Thus, we may infer that there is an association between venture size

and entrepreneurs place of origin.

TABLE 4.23

TYPE OF BUSINESS AND THEIR PLACE OF ORIGIN

Entrepreneurs’ place of origin Chi –

Square Category of Tourism Business

Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total

Hotels 9

(36.0%) 9

(36.0%) 0

(.0%) 6

(24.0%) 1

(4.0%) 25

(100.0%)

Restaurants 13

(56.5%) 5

(21.7%) 1

(4.3%) 3

(13.0%) 1

(4.3%) 23

(100.0%)

Travel Agencies/Tour Operators

8 (13.6%)

41 (69.5%)

7 (11.9%)

3 (5.1%)

0 (.0%)

59 (100.0%)

Transport Operator

8 (36.4%)

8 (36.4%)

4 (18.2%)

2 (9.1%)

0 (.0%)

22 (100.0%)


5 (14.3%)

14 (40.0%)

7 (20.0%)

9 (25.7%)

0 (.0%)

35 (100.0%)


4 (11.1%)

19 (52.8%)

2 (5.6%)

4 (11.1%)

7 (19.4%)

36 (100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

72.191 .000


Table 4.23 shows, that the relationship between the type of business and

the domicile status of the respondents was significant. It shows among the 25

hotels, 9 were run by Kanadiga and other 9 were run by non Kanadigas.

Similarly, in the transport operator category, out of 22 units 8 were operated by

Kanadigas and 8 were operated by non Kanadigas. In the restaurant category

out of 23 units the Kanadiga dominated with 13 as against 5 by non Kanadiga

167

respondents. In the other categories, the non Kanadiga outnumbered the locals.

The overall trend was that restaurant business needed the local market,

location, manpower knowledge and provisions procurement abilities and thus

the Kanadigas were comfortable in this segment of business. In the business

like travel agencies, tourism vendors and entertainment service providers, the

migrants far outnumber the locals. The later mentioned categories require

professional expertise with global networking that the migrants could bring

with them. The variables, categories of business and entrepreneurs place of

origin are thus associated. The significance value of the chi-square test is .000,

indicating that the null hypothesis is rejected. This confirms the fact the type of

business has association with the entrepreneurs’ place of origin.

TABLE 4.24

ORGANIZATIONAL STRUCTURE AND

RESPONDENTS PLACE OF ORIGIN

Entrepreneurs’ place of origin Chi-

Square Organization

Structure Local

Kanadiga Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total

Single Unit 28

31.5%) 34

(38.2%) 9

(10.1%) 13

(14.6%) 5

(5.6%) 89

(100.0%)

Branches in Karnataka

16 (40.0%)

12 (30.0%)

6 (15.0%)

6 (15.0%)

0 (.0%)

40 (100.0%)

Branches in Other States

3 (5.2%)

45 (77.6%)

3 (5.2%)

5 (8.6%)

2 (3.4%)

58 (100.0%)

Branches in Overseas

0 (.0%)

5 (38.5%)

3 (23.1%)

3 (23.1%)

2 (15.4%)

13 (1 00.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

45.659 .000


168

With regard to the structure of the unit in terms of its spread of

operations, namely whether the business operates from a single location or

multiple locations, the results as shown in Table 4.24, reveal that close to half

of the sample respondents (89 out of 200) have their business in a single

location, followed by (58 out of 200) respondents who have branches in other

states as well. Interestingly, immigrant respondents were found to have their

business in multiple locations. The NRIs (both local and immigrant) have their

units at both single and multiple locations.

The Chi–square test shows significance value of .000 and thus the null

hypotheses can been rejected. It can be concluded as entrepreneurs’

organization structure and their place of origin are connected in many ways.

TABLE 4.25

MOTIVATION AND RESPONDENTS PLACE OF ORIGIN

Respondents place of origin

Motivation to Start Entrepre-

neurship

Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total Chi-Square

Urge to Achieve

24 (21.4%)

56 (50.0%)

11 (9.8%)

14 (12.5%)

7 (6.3%)

112 (100.0%)

Excess Funds 4 (22.2%)

9 (50.0%)

1 (5.6%)

4 (22.2%)

0 (.0%)

18 (100.0%)


6 (14.0%)

24 (55.8%)

4 (9.3%)

7 (16.3%)

2 (4.7%)

43 (100.0%)


1 (16.7%)

3 (50.0%)

2 (33.3%)

0 (.0%)

0 (.0%)

6 (100.0%)


12 (57.1%)

4 (19.0%)

3 (14.3%)

2 (9.5%)

0 (.0%)

21 (100.0%)

Total 47 (23.5%)

96 (48.0%)

21 (10.5%)

27 (13.5%)

9 (4.5%)

200 (100.0%)

25.427.003


169

Enterprise creation is the result of an individual’s motivation. Table 4.25

reveals that 112 members out of 200 respondents were drawn into business by

the ‘urge to achieve’. Thus, more than half of the respondents were driven by

David McClelland’s Need to achieve motivation. Family financial support also

played an important role in motivating many local entrepreneurs as their roots,

family, friends were all in Bangalore. Professional expertise was the second

highest motivation with 43 out of 200 respondents. In that order was the

avaibility of surplus funds. In this case the respondents were mostly NRIs with

sizable savings. It is clear that motivation to start entrepreneurship is connected

to entrepreneurs’ place of origin in many ways. The chi-square test shows the

significance value is .003, denoting the null hypotheses should be rejected

thereby confirming there is valid association between entrepreneurs’ place of

origin and motivation.

TABLE 4.26

RESPONDENTS DISPOSITION TOWARDS INNOVATION

Respondents place of origin Innovation in

Tourism Industry Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total Chi-square

No Changes 16

(39.0%) 17

(41.5%) 4

(9.8%) 3

(7.3%) 1

(2.4%) 41

(100.0%)

Introduced New Concept

13 (24.5%)

24 (45.3%)

7 (13.2%)

6 (11.3%)

3 (5.7%)

53 (100.0%)

Experimented with New Concept But Failed

2 (13.3%)

9 (60.0%)

2 (13.3%)

2 (13.3%)

0 (.0%)

15 (100.0%)

Successful in Exploiting New Ideas

10 (20.8%)

23 (47.9%)

7 (14.6%)

8 (16.7%)

0 (.0%)

48 (100.0%)

Revolutionized the Existing System

6 (14.0%)

23 (53.5%)

1 (2.3%)

8 (18.6%)

5 (11.6%)

43 (100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

20.459 .015


170

With regard to the respondents’ disposition towards their attitude to new

ideas and innovations, Table 4.26 shows that 53 out of 200 respondents

introduced new concepts now and then. This trend has signs of Peter Drucker’s

argument that innovation is the main ingredient for entrepreneurship.1 48 out of

200 respondents claimed they were ‘successful in exploiting untapped

demand’. Whereas 43 respondents claimed they ‘revolutionized the existing

system’. This had signs of Joseph Schumpeter’s thesis ‘creative destruction’.2

There were 14 out of 200 who claimed the ‘experimented with new concept but

failed’ but are still successful about their business. The chi–square test shows

significance value of .015 and therefore the null hypothesis is rejected.

TABLE 4.27

VENTURE GROWTH AND PLACE OF ORIGIN OF RESPONDENTS

Entrepreneurs’ place of origin Chi-

Square Progress in the

Business Local

Kanadiga Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total

Loss making

4 (36.4%)

2 (18.2%)

1 (9.1%)

3 (27.3%)

1 (9.1%)

11 (100.0%)

Break Even

6 (21.4%)

16 (57.1%)

1 (3.6%)

5 (17.9%)

0 (.0%)

28 (100.0%)

Moderate Profit

29 (27.6%)

48 (45.7%)

13 (12.4%)

7 (6.7%)

8 (7.6%)

105 (100.0%)

High Profit

8 (14.3%)

30 (53.6%)

6 (10.7%)

12 (21.4%)

0 (.0%)

56 (100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

23.010 .028


171

Table 4.27, shows, growth of business and place of domicile. It may be

seen that immigrant entrepreurs seen to be doing well compared to the native

entrepreneurs. Migrants were double in number than the locals in making

moderate profits. Again they were four times their local counterparts in

making good profits. 11 out of 200 were making loss and were prepared to

close down or change their business. Thus it is evident that the adage survival

of the fittest holds good in Bangalore tourism industry. The chi-square test

produces the significance value of .028, indicating the null hypothesis is

rejected.

TABLE 4.28

COMPETITION AND PLACE OF ORIGIN OF RESPONDENTS

Origin of Domicile Chi-

Square Strong

Competition Local

Kanadiga Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total

Yes 37

(23.0%) 77

(47.8%) 17

(10.6%) 24

(14.9%) 6

(3.7%) 161

(100.0%)

No

10 (25.6%)

19 (48.7%)

4 (10.3%)

3 (7.7%)

3 (7.7%)

39 (100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

4.389 .495


Table 4.28 demonstrates, 161 respondents out of 200, claim they faced

strong competition. 161 respondents answered ‘yes’ with regarde to the

competition they face in the business ‘yes’ The overall picture emerging is

immaterial of their place of origin the entrepreneurs were subject to

competition and a few were not subject to competition. The chi–square test of

significance gives a result of .495 showing the null hypotheses is not rejected.

172

TABLE 4.29

BRAND BUILDING AND RESPONDENTS PLACE OF ORIGIN Entrepreneurs’ place of origin

Brand Building

Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total Chi-

Square

Yes 24

(17.5%) 73

(53.3%) 14

(10.2%) 22

(16.1%) 4

(2.9%) 137

(100.0%)

No 23

(36.5%) 23

(36.5%) 7

(11.1%) 5

(7.9%) 5

(7.9%) 63

(100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

13.708 .008


The relationship between brand building and place of origin as shown in

Table 4.29, demonstrates an overwhelming 137 members out of 200 agreeing

they are very keen in brand building. The migrants were three times than that of

the locals in the act of building brands. This again shows the migrant

entrepreneurs were more professional and resorted to more aggressive

marketing. An interesting find is equal number of locals saying yes and also no

to brand building. The chi-square test show the significance value of .008,

which indicates the null hypothesis is rejected.

TABLE 4.30

BREAK –EVEN PERIOD AND RESPONDENTS PLACE OF ORIGIN

Respondents place of origin Chi-

Square Break Even

Period Local

Kanadiga Local Non-Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals Total

Within One Year

14 (21.9%)

32 (50.0%)

6 (9.4%)

5 (7.8%)

7 (10.9%)

64 (100.0%)

2-5 Years

25 (23.1%)

51 (47.2%)

13 (12.0%)

17 (15.7%)

2 (1.9%)

108 (100.0%)

6-10 Years

8 (28.6%)

13 (46.4%)

2 (7.1%)

5 (17.9%)

0 (.0%)

28 (100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

12.252 .140


173

The study of break-even period and place of domicile was significant to

test the business prudence of the operators. Table 4.30 projects 54% of the

respondents took 2-5 years; and 32% of the respondents took a year for the feat.

This shows that majority (86%) of the tourism entrepreneurs of Bangalore

could break even very early, i.e., within the first 5 years. Within this early

break-even period of less than 5 years there are 39 local players and 83

migrants. Once more the results show that the migrants are more aggressive in

business. Another interesting fact is that 7 out of total 9 foreigners could break

even within a year. This show the foreigners were in less capital outlay and

high return on investment ventures, mostly in IT solutions to the tourism

industry. The chi–square test produces the significance value of .140

suggesting the null hypothesis is not rejected.

TABLE 4.31

VENTURE LIFE SPAN AND RESPONDENTS PLACE OF ORIGIN

Respondents place of origin Chi-

Square Venture Life Span

Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total

One Year

15 (37.5%)

16 (40.0%)

1 (2.5%)

4 (10.0%)

4 (10.0%)

40 (100.0%)

2- 4 Years

15 (17.6%)

42 (49.4%)

12 (14.1%)

12 (14.1%)

4 (4.7%)

85 (100.0%)

5-10 years

17 (22.7%)

38 (50.7%)

8 (10.7%)

11 (14.7%)

1 (1.3%)

75 (100.0%)

Total 47 (23.5%)

96 (48.0%)

21 (10.5%)

27 (13.5%)

9 (4.5%)

200 (100.0%)

13.607 .093


Table 4.31, shows that the maximum number of ventures (42.5%) were

operating for 2-4 years; and 37.5% of them were there for 5-10 years; leaving

174

the balance 20% to the less than 1 year group. Likewise the NRIs (Local and

migrants) were also scattered non uniformly in all categories of venture life

span. Thus no logical relationships could be established between the variables.

The chi–square test produced significance value of .093; denoting the null

hypotheses cannot be rejected.

TABLE 4.32

MOTIVATION TO START VENTURE AND RESPONDENTS

PLACE OF ORIGIN


Chi-Square Test

Motivation to Start

Entrepreneurship Local

Kanadiga Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total

Urge to Achieve 24

(21.4%) 56

(50.0%) 11

(9.8%) 14

(12.5%) 7

(6.3%) 112

(100.0%)

Excess Funds 4

(22.2%) 9

(50.0%) 1

(5.6%) 4

(22.2%) 0

(.0%) 18

(100.0%)


6 (14.0%)

24 (55.8%)

4 (9.3%)

7 (16.3%)

2 (4.7%)

43 (100.0%)


1 (16.7%)

3 (50.0%)

2 (33.3%)

0 (.0%)

0 (.0%)

6 (100.0%)


12 (57.1%)

4 (19.0%)

3 (14.3%)

2 (9.5%)

0 (.0%)

21 (100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

25.427 .063


Table 4.32 shows that entrepreneurial motivation spread across the place

of origin revealed the migrants were double the number than the locals in terms

of ‘urge to achieve’ and they were four times than that of their local

counterparts in ‘professional expertise’ Thus, migrants by and large had much

more work experience that channelised their thinking to start the units. Almost

all the NRI (local and from other states) were motivated by ‘the urge to

175

achieve’. The NRI population in Bangalore was sizeable and they brought with

them the knowledge and gained by working overseas. The foreign nationals

also were mostly driven by the achievement factor (77.8%) and professional

expertise (22.2%) in their respective category. The chi-square test show

significance value of .063 that is more than .050 and thus the null hypothesis of

the variables not being related are not rejected.

TABLE 4.33

INNOVATIONS AND ENTREPRENEURS’ PLACE OF ORIGIN


Innovations in Tourism Industry

Local Kanadiga

Local Non-

Kanadiga NRI

Kanadiga NRI Non Kanadiga

Foreign Nationals

Total Chi-

Square

No Changes 16

(39.0%) 17

(41.5%) 4

(9.8%) 3

(7.3%) 1

(2.4%) 41

(100.0%)

Introduced New Concepts

13 (24.5%)

24 (45.3%)

7 (13.2%)

6 (11.3%)

3 (5.7%)

53 (100.0%)

Experimented with New Concept But Failed

2 (13.3%)

9 (60.0%)

2 (13.3%)

2 (13.3%)

0 (.0%)

15 (100.0%)

Successful in Exploiting New Ideas

10 (20.8%)

23 (47.9%)

7 (14.6%)

8 (16.7%)

0 (.0%)

48 (100.0%)

Revolutionized the Exiting System

6 (14.0%)

23 (53.5%)

1 (2.3%)

8 (18.6%)

5 (11.6%)

43 (100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

20.459 .015


Table 4.33 shows, the degree of changes effected by respondents in their

respecting business. 41 respondents out of 200 did not make any change and

were busy with their routine. On the whole immigrant enterprises were more

adept in the introducting and adapting to changes. The chi–square test produced

the significance value of .015 suggesting the null hypothesis is rejected.

176

TABLE 4.34

PERCEPTION OF COMPETITION AND RESPONDENTS PLACE OF

ORIGIN

Origin of Domicile Strong

Competition Local Kanadiga

Local Non-

Kanadiga

NRI Kanadiga

NRI Non Kanadiga

Foreign Nationals

Total Chi-

Square

Yes 37

(23.0%) 77

(47.8%) 17

(10.6%) 24

(14.9%) 6

(3.7%) 161

(100.0%)

No 10

(25.6%) 19

(48.7%) 4

(10.3%) 3

(7.7%) 3

(7.7%) 39

(100.0%)

Total 47

(23.5%) 96

(48.0%) 21

(10.5%) 27

(13.5%) 9

(4.5%) 200

(100.0%)

4.389 .495


Enterprenurs’ perception of competition as revealed by Table 4.34

shows uniform distribution of yes and also no responses as. The ratio of the

migrants to locals was 2:1 in both the categories of yes and no responses. The

yes and no scores were in the ratio of 4:1. The chi-square test produced

significance value of .495 suggests that the null hypothesis is not rejected.

In the study of the effect of the entrepreneurs place of origin on the type

of business, organizational structure, motivation, and changes brought, venture

growth, competition, brand building, break-even period and venture life span, it

was found that place of origin had good association with almost all the aspects.

In a few cases (four) the chi-square test did not reject the null hypotheses and

these results were close to 0.05 suggesting marginality. Thus, it can conclude

that there is considerable association between the entrepreneurs’ place of origin

and the factors determining the scope of success in diverse entrepreneurial

ventures in the tourism industry.

177

Comparatively, age has stronger association than gender and place of

origin in influencing the birth, growth progress and success of entrepreneurial

businesses.

HO: There is no significant association between the place of origin of the

entrepreneurs and the factors determining the scope for success in

the diverse entrepreneurial ventures in tourism industry.

The above mentioned null hypothesis is thus rejected.

Business Performance of the Respondents

An attempt was also made to find out several factors that are responsible

for the growth of ventures. In order to survive in a highly competitive

international market a good amount of marketing efforts are required. The

relationship between type of business, brand building and competition they

encountered, have been analyzed. Subsequently, to examine the business

performance, the break-even period and the life span of the business are studied

in relation to the type of business. The results and interpretations are presented

below.

TABLE 4.35

TYPES OF BUSINESS AND BRAND BUILDING

Brand Building Category of Tourism Business Yes No Total

Chi-Square test

Hotels 20 (80.0%) 5 (20.0%) 25 (100.0%)

Restaurants 14 (60.9%) 9 (39.1%) 23 (100.0%)


44 (74.6%) 15 (25.4%) 59 (100.0%)

Transport Operator 9 (40.9%) 13 (59.1%) 22 (100.0%)


27 (77.1%) 8 (22.9%) 35 (100.0%)


23 (63.9%) 13 (36.1%) 36 (100.0%)

Total 137 (68.5%) 63 (31.5%) 200 (100.0%)

12.490 .029


178

There was an overwhelming response to the need for brand building

with 137 units agreeing out of 200 respondents who were aware of the branding

exercise and its usefulness to business. Tourism business vendors however out

number other category of enterprineurs (77%) with regard to the effort put in

branding the products. Bangalore as such and the inhabitants are branded

conscious. Entrepreneurs are aware of this and all the categories of

entrepreneurs have executed their efforts to build and popularize their brands.

Vendors seen to have realized the need for branding quite well as they have to

establish strong relationship with the entrepreneurs based on the credibility of

brand. The chi-square test shows significance value of .029 which explains that

the null hypothesis (of the variables not related) is rejected.

TABLE 4.36

TYPE OF BUSINESS AND COMPETITION

Category of Tourism Business Strong

Competi-tion

Hotels Restau-rants

Travel Agencies/

Tour Operators

Trans-port

Operator


Entertainment Service

Providers

Total Chi-Square Tests

Yes 21

(13.0%) 20

(12.4%) 48

(29.8%) 17

(10.6%) 30

(18.6%) 25

(15.5%) 161

(100.0%)

No 4

(10.3%) 3

(7.7%) 11

(28.2%) 5

(12.8%) 5

(12.8%) 11

(28.2%) 39

(100.0%)

Total 25

(12.5%) 23

(11.5%) 59

(29.5%) 22

(11.0%) 35

(17.5%) 36

(18.0%) 200

(100.0%)

4.389 .495


The results in Table 4.36 clearly show a large majority of the

entrepreneurs, (161 out of 200) encounter strong competition in their business.

179

All the categories of entrepreneurs are facing the competition without

exception.

Similarly, the establishments that claimed no competition, (39 out of

200) are distributed across all the categories. It is clear that the nature of

business does not have any bearing on having the degree of competition. The

chi-square test shows a significance value of .495 which denotes the null

hypothesis of the variables not related, is not rejected.

TABLE 4.37

TYPE OF BUSINESS AND BREAK-EVEN PERIOD

Break even time period of the ventures Chi-

Square Category of

Tourism Business

Within One Year

2-5 Years 6-10 Years Total

Hotels 3 (12.0%) 12 (48.0%) 10 (40.0%) 25 (100.0%)

Restaurants 13 (56.5%) 9 (39.1%) 1 (4.3%) 23 (100.0%)


23 (39.0%) 28 (47.5%) 8 (13.6%) 59 (100.0%)

Transport Operator

7 (31.8%) 15 (68.2%) 0 (.0%) 22 (100.0%)


5 (14.3%) 27 (77.1%) 3 (8.6%) 35 (100.0%)


13 (36.1%) 17 (47.2%) 6 (16.7%) 36 (100.0%)

Total 64 (32.0%) 108 (54.0%) 28 (14.0%) 200 100.0%)

35.751 .000


Tourism business is vast and of diverse nature where all the categories

have complete different style of operations. Table 4.37 clearly shows that an

airline is the most capital intensive industry, next come the hotels, the tourism

vendors, the restaurants, transport services. The travel/tour services are perhaps

180

the least capital intensive. Further, it is interesting to note that 10 out of 25

hotels (40%) needed 6-10 years to break even. Whereas 56.5% of the

restaurants brokeeven within one year. 47.2% of the travel agents took 2-5

years to break even. Similarly 68.2% of the transport operator needed 2-5 years

to break even. Tourism vendors with 77.1% and Entertainment service

providers with 47.2% both needed 2-5 years to break even. Thus we can see the

hotel industry is the most capital intensive and has moderate return on

investment with relatively longer period break-even. Restaurants are less

capital intensive and have higher return on investment with low break even

period. The other categories like transport, vendors and entertainment have

proportionate capital investment and return on investment and break-even

period is 2-5 years. The chi–square score shows a significance value of .000

that suggests the null hypothesis stands rejected.

TABLE 4.38

TYPE OF BUSINESS AND LIFE SPAN

Venture Life Span Chi-

Square Category of Tourism

Business One Year 2- 4 Years 5-10 years Total

Hotels 9 (36.0%) 7 (28.0%) 9 (36.0%) 25 (100%)

Restaurants 11 (47.8%) 10 (43.5%) 2 (8.7%) 23 (100%)


9 (15.3%) 29 (49.2%) 21 (35.6%) 59 (100%)

Transport Operator 3 (13.6%) 9 (40.9%) 10 (45.5%) 22 (100%)


2 (5.7%) 13 (37.1%) 20 (57.1%) 35 (100%)


6 (16.7%) 17 (47.2%) 13 (36.1%) 36 (100%)

Total 40 (20.0%) 85 (42.5%) 75 (37.5%) 200 (100%)

28.432 .002


181

The study on venture life span is necessary to understand the longivity

of the ventures. As could be seen Table 4.38 apart from the restaurants all other

ventures were in business for 5-10 years. Thus, the tourism enterprises had a

fairly long life span. The scores also show there were many new establishments

in all the categories which are just one year old. The overall objective of the

study was to find out the life span of the units for the last 10 years of the

liberalization period. Result show that new units were established almost every

year during the last 10 years. All these units were operating successfully. The

chi–square result shows the significance value at .002 that indicates the null

hypothesis is rejected.

Friedman Mean Rank Chi–Square test application

Some of the major ingredients that influence the creation and success of

business are sources of capital, promotional measures, type of tourism business,

reasons for success, and obstacles faced, if any, need to be examined in detail.

Following hypothesis has been introduced and Friedman mean rank Chi-Square

test is applied.

H5: Items with the mean rank value representing sources of capital,

business promotion, nature of tourism business, reason for success

and obstacles are independent to each other.

An attempt is made to rank the various aspects under each head,

according to its order of importance and investigate the reasons for its

respective position. Further, it was also attempted to find out whether all these

individual factors are related or independent.

182

TABLE 4.39

STATEMENT OF MEAN RANK OF SOURCES OF

CAPITAL AND CHI–SQUARE TEST

Sources of Capital Mean Rank Chi-Square

Own Fund 4.90

Banks 4.00

Financial Institutions 4.00

Friends and Relatives 2.40

Venture Capitals 3.40

Personal Loan 2.30

12.427

Sig..029

Friedman Test. Source: Primary Data.

The study of the sources of capital as shown in Table 4.39 reveals that

the most frequently used source of capital is own funds, followed by funds

supplied by banks and financial institutions. Among these various sources, own

funds stands as the most important and mostly utilized at the mean rank of

4.90. Entrepreneurs by and large use their own funds to maintain control and

the next options are the traditional banks at 4.00 and financial institutions also

at 4.00. The financial environment of Karnataka in general and Bangalore in

particular is quite positive, where funding from financial institutions for the

various business proposals is liberal. The emergence of venture capital is also

evident as the next indicator at the mean rank of 3.40. Truly, venture capitalists

of national and international fame have set their shops successfully in

Bangalore. The funds supplied by friends and relatives (2.40) and personal

loans (2.30) are less sought after options. It shows that entrepreneurs are

professional minded and have self-confidence to mobilize resources through

institutional means. The chi–square test show the significance value of .029

183

which indicates the variables are independent to each other, but they are all

significant interms of sources of business funds.

TABLE 4.40

MEAN RANK OF BUSINESS PROMOTION AND CHI-SQUARE TEST

Business Promotion Mean Rank Chi–square test

Advertising 3.56

Electronic Channel 2.91

Physical Channel 2.72

Sales Promotion 2.69

Personal Selling 3.11

40.268

.000


Data related to business promotion as shown in Table 4.40 reveals that

the most popular method adopted is advertising at the mean rank of 3.56.

Tourism business requires extensive use of advertising in all possible Medias.

Posters, banners, visual representations and cinema/video presentations can

truly project the spirit of tourism. Personal selling or direct marketing score the

second highest position of mean rank with 3.11. Today the travel and tourism

trade believe in approaching the customers directly in person, through

telephone or through the internet. The electronic channel is indicated as the

third most popular method at 2.91 where the website reservations, CRS, GDS

and all other online marketing forms come in. International tourism requires

fast and high level of networking. The next mean rank is occupied by physical

channel at 2.72 where the wholesalers and retailers play their role. Travel

agents, hotels, vendors, entertainment providers all use this at different levels.

The lowest of mean rank is held by sales promotion at 2.69. The indicator is

184

close to other methods, signifying all tourism entrepreneurial units use personal

selling in a less frequent manner. The chi–square test result produces a

significance value of .000 that show each of the various promotion methods is

independent and does not affect each other. But collectively they constitute

important promotional measures.

TABLE 4.41

MEAN RANK OF TOURISM TYPES WITH

CHI-SQUARE TEST

Tourism Types Mean Rank Chi-Square

Transit to Mysore 4.15

Urban Tourism 1.86

Business Tourism 4.10

Leisure Tourism 1.83

Medical Tourism 3.07

419.204 Sig.000


The mean rank Table 4.41, shows ‘Transit to Mysore’ with highest

position with the mean rank 4.15. Bangalore traditionally is the entry point for

Bangalore–Mysore–Ooty itinerary. This still holds good and many a

businessman in tourism industry commercially exploit the same. Business

tourism has surprisingly come second in rank with 4.10; contrary to the popular

belief that it should be the first. The importance of business in Bangalore has

been discussed in chapter III. Medical tourism scores the third rank with 3.07

showing the emerging new trend in Bangalore. Wellness/health/medical

tourism is fast gaining grounds with a number of health therapy centers, spas,

nursing homes and world class hospitals.3 This is followed by urban tourism at

1.86 and leisure tourism at 1.83 with close scores. The study reveals there are

185

significant urban tourism and leisure tourism happenings and the presence of

several attractions that draw tourists to Bangalore. The chi-square test result at

.000 signifies all these individual aspects are not related to each other; but all

together they form the tourism business scope the entrepreneur can promote

and serve.

TABLE: 4.42

MEAN RANK OF REASONS FOR VENTURE SUCCESS AND

CHI-SQUARE TEST

Reason for success Mean Rank Chi-Square

Strong Unique Selling Proposition 2.91

Aggressive Marketing 2.49

Tenacity and Dedication 4.30

Constant Product Development 2.27

Good Financial Management 3.03

.422 Sig. .000


As regards the contributing factors for success (Table 4.42), tenacity and

dedication take the highest rank (4.30). The capacity to meet all odds and still

keep the venture going is clearly indicated by most of the respondents as the

strongest. Good financial management comes second (3.03) as competition is

intensifying by the day. Strong USP (2.91) comes next as market forces are

high and the product has to be unique, given the growing competition.

Aggressive marketing (2.49) and constant product development (2.27) comes

next in the order once again shows the compulsions of market forces. The

significant finding tenacity and dedication is rated by the respondents’ way

above all the other qualities. That shows hard work and perseverance pay in the

long run and contribute immensely for success. The chi–square significance

186

value is .000 showing the factors are individual and not connected to each other

but together they decide the entrepreneurial success.

TABLE 4.43

MEAN RANK OF LIMITATIONS/BARRIERS

TO VENTURE AND CHI-SQUARE TEST

Limitations/Barriers Mean Rank Chi-Square

Bureaucratic hurdles 4.37

Increasing cost of business 4.80

Dominance of MNC 4.06

Attrition 3.88

Civic Problems 2.60

Personal Problems 1.31

485.703 Df

Sig. .000


As regards the limitations/barriers faced by the entrepreneurs as could

be seen in Table 4.43, the highest mean rank is occupied by ‘increasing cost of

businesses at 4.80. This reflects the fact that Bangalore is the costliest city in

India. All the respondents opined this as the greatest hurdle they confront with.

Next in close order comes ‘bureaucratic hurdle’ at 4.37 and ‘dominance of

MNCs’ at 4.06. Some of the state government policies are restrictive that

hamper the growth of business. The entry of multinationals has further added to

the woes of the respondents as many find it difficult to face the competition

from the MNCs as they bring in advanced technology and huge resources.

Attrition/staff problems were the next barrier, at 3.88 followed by civic

problems with 2.60 and personal problems as last at 1.31. The tourism staff was

skilled and good in communication skills and thus tended to change jobs

frequently. Frequent power cuts, bad roads, traffic jams, and over population

187

have given enough grounds for civic problems. The chi-square result shows

significance value of .000 suggesting that all these factors ranked are individual

and do not have connection between one and other. But they create obstacles to

the entrepreneurs.

Target Market for Tourism Entrepreneurs

A clear picture emerges regarding the business promotion methods and

the types of tourism business the entrepreneurs were engaged in and also the

reason for their success and the hurdles they faced. Target markets that

produced tourists and kept the entrepreneurs in business had to be investigated.

Secondary data sources produced data on international tourism that can be

exploited by the entrepreneurs.

In 2007 there were over 903 million international tourist arrivals, with a

growth of 6.6% as compared to 2006. International tourist receipts were USD

856 billion in 2007. Despite the uncertainties in the global economy,

international tourist arrivals during the first four months of 2008 followed a

similar growth trend.

However, as a result of economic crisis of 2008, international travel

suffered a strong slowdown beginning in June 2008, with growth in

international tourism arrivals worldwide falling by 2% during the Boreal

summer, while growth from January to April 2008 had reached an average

5.7% compared to its 2007 level. Growth from 2006 to 2007 was 3.7%, as total

international tourism arrivals from January to August were 641 million tourists,

up from 618 million in the same period in 2007.4

188

The country specific and India’s standing in the global tourism scenario

is presented below. The World Tourism Organization reports the following 10

countries as the most visited in 2007 by number of international Tourists:

TABLE 4.44

MOST VISITED COUNTRIES

Rank Country UNWTO Regional Market

International Tourist Arrivals

(2007)

International Tourist Arrivals

(2006)

1 France Europe 81.9 million 79.1 million

2 Spain Europe 59.2 million 58.5 million

3 United States North America 56.0 million 51.1 million

4 China Asia 54.7 million 49.6 million

5 Italy Europe 43.7 million 41.1 million

6 United Kingdom Europe 30.7 million 30.7 million

7 Germany Europe 24.4 million 23.6 million

8 Ukraine Europe 23.1 million 18.9 million

9 Turkey Europe 22.2 million 18.9 million

10 Mexico North America 21.4 million 21.4 million

Source: United Nations World Tourism Statistics, 2007.

In the above list the extract showing only the top ten, as per Table 4.44

India ranks 42nd with 5 million international arrivals, tying up with Brazil

placed at 41st with the same 5 million international tourists arrivals, during

2007.

It was essential to find out the business volume of tourism that the

prominent nations were doing as mere arrivals did not reflect the bulk of

revenue earned from tourism. Thus studies on total earnings from tourism by

leading nations were collected through secondary data sources.

189

TABLE 4.45

INTERNATIONAL TOURISM RECEIPTS

Rank Country UNWTO Regional

Market

International Tourist Receipts

(2007)

International Tourist Receipts

(2006)

1 United States North America $ 96.7 billion $ 85.7 billion

2 Spain Europe $ 57.8 billion $ 51.1 billion

3 France Europe $ 54.2 billion $ 46.3 billion

4 Italy Asia $ 42.7 billion $ 38.1 billion

5 China Europe $ 41.9 billion $ 33.9 billion

6 United Kingdom Europe $ 37.6 billion $ 33.7 billion

7 Germany Europe $ 36.0 billion $ 32.8 billion

8 Australia Oceania $ 22.2 billion $ 17.8 billion

9 Austria Europe $ 18.9 billion $ 16.6 billion

10 Turkey Europe $ 18.5 billion $ 6.9 billion

Source: United Nations World Tourism Organization statistics 2007.5

Statistical records show that the most visited countries are not the same

as highest tourism revenue earnings generating countries. As far as the tourism

receipts are concerned as shown in Table 4.45, United States takes the

undisputed lead by earning 96.7 billion dollars during 2007 as against 85.7

billion during 2006. Thus it was essential to study the highest spending

countries in tourism activities. The high spending countries reflect the potential

for foreign tourists who would actually generate international tourism. The high

spending countries would be of marketing interest to India and to other

countries aspiring to make it big in global tourism.

190

TABLE 4.46

INTERNATIONAL TOURISM TOP SPENDERS

Rank Country UNWTO Regional Market

International Tourist

Expenditure (2007)

International Tourist Expenditure (2006)

1 Germany Europe $ 82.9 billion $ 73.9 billion

2 United States North America $ 76.2 billion $ 72.1 billion

3 United Kingdom Europe $ 72.3 billion $ 63.1 billion

4 France Europe $ 36.7 billion $ 31.2 billion

5 China Asia $ 29.8 billion $ 24.3 billion

6 Italy Europe $ 27.3 billion $ 23.1 billion

7 Japan Asia $ 26.5 billion $ 26.9 billion

8 Canada North America $ 24.8 billion $ 20.5 billion

9 Russia Europe $ 22.3 billion $ 18.2 billion

10 South Korea Asia $ 20.9 billion $ 18.9 billion

Source: United Nations World Tourism Organization Statistics 2007.

The World Tourism Organization sources present that for the 5th year in

a row, German tourists continue as the top spenders as presented in Table 4.46.

A study by Dresdner Bank forecasted that for 2008, Germans and Europeans in

general will continue to be the top spenders, because of the strength of the Euro

against the U.S. dollar–with strong demand for U.S. destinations rather than

others.6

The WTO statistics further show that France and Spain attract tourists

most and get the maximum tourist arrivals. In fact 9 destinations that have huge

volume of business are European. All these European tourist destinations such

as as France, Spain, Italy, United Kingdom, Germany Ukraine, Russia, Austria

and Turkey are rich in their unique cultures and possess multi attractions for

191

tourists. Various interviews with international tourists reveal the attractions in

their mind about the European destinations as follows.

France – Artists paradise – painting, sculpting, folk music, theatre,

street performers. Enchanting Country side; the best wine regions of the world;

Unending valleys of vineyard; Lovers and honeymooner's paradise;

mesmerizing perfumes; the unforgettable French Cuisine that perhaps taught

the world the culinary art and skills; an old and rich history; Mecca for fashion

designing and also the modern vibrating night life of Paris.

Spain – Glorious history, beautiful architecture; beautiful people with

colorful customs as costumes; music; dance forms and lifestyle vibrant

festivals; traditional bull fight and bull taming sports; rich cuisine with full

bodied wine and exciting spirits; modern tourist entertainments and nightlife.

Italy – The Glorious Roman history; the ruins of the Roman Empire; the

warm sunshine and cool breeze of the Mediterranean region; the vineyards of

the Tuscany region; the distinctive Italian cuisine with the wines; the touch of

artistic class with paintings, sculptures that draw its heritage from Michael

Angelo and Leonardo Da Vinci; the romance of the Gondolas in Venice; and

the ultimate religious haven for Christians at the Papal abode of the Vatican

City.

The rest of the 6 destinations are also endowed with multi attractions

that are spread over a wide spectrum and each unique in itself. The other

interesting feature was, all these European destinations had the best modern

transportation, the best hotels and the state of art tourist facilities. This lesson

192

should be learnt by promoters of Indian tourist destinations and the tourism

service providing entrepreneurs. Tourists rush to destinations that are unique

and are capable of offering a package, that can provide existing experience in

culture, architecture, music, dance, nature, weather, food, wine and spirits,

sports, entertainment, people and their lifestyle – it is the total unique

experience that makes a Country a top tourist destination. All these should be

backed up by upgraded modern tourists' facilities to suite the quality conscious

global traveler.

The next interesting analysis made is most of these European

destinations together with United States and three Asian destinations with

Australia feature in all the three tables. This shows there is a strong relationship

between the most popular destinations, the highest tourism revenue earning

nations, and the highest tourism spending nations. The Global tourism

consciousness seems to be polarized on this group of countries where the

highest traffic, the highest spending, and the highest receipts take place. So

when the respondents opined that tourism will grow globally and will be

concentrated in a few countries in years to come, they were correct and aware

of the actual happenings.

A stark reality that automatically emerges is that China ranks 4th in most

visited destinations and 5th in top Tourism Receipts and the Top Tourism

Spenders simultaneously. China proves to be one of the most successful

nations, attracting tourists as well as spending on tourism and earning from

tourism. In Asia, what China possess India does not possess? This question

193

should work on all tourism professional's mind, including the entrepreneurs.

China apparently having a not so open culture, conservative communist

ideology, population not so conversant in English language and not an expert in

international affairs – could achieve such a feat in international tourism. In the

light of all these, it is differenting to note that India is found lagging at an

insignificant 42nd position in Global tourism ranking. Observation and

interviews with tourists and employees of tourism units reveal that China is

endowed with certain unique strengths like very old history and culture,

Mongolian – Buddhism – Communism – Neo Capitalism evolution, Popular

Chinese Cuisine. Chinese art, craft, dances, festivals, Chinese mysticism,

popular martial arts and sports. This is backed up with modern tourism

facilities of Beijing, Hong Kong and Shanghai that sports world class airports,

hotels and transportation. The neighboring popular hub of Singapore has added

to the popularity of Chinese tourism circuit. So the above mentioned analysis

holds good for China. China's silent success of global tourism can be a strong

case study for India. A number of questions should be raised and solutions

achieved, before India can really match China in economic development, in

global tourism or in hosting the Olympics.

As discussed earlier, it is high time that tourism entrepreneurs evolved

strategies focused on specific markets. Travel agents, tour operators, hotels and

airlines can target the lucrative markets of Germany, United States, United

Kingdom, France, China, Italy, Japan, Canada, Russia and South Korea. These

nationals are the top spenders in tourism activities and their demands have to be

194

met to ensure their patronage. The entrepreneurs should study tourism demand

determinants like preference of region, weather, and scenic beauty, preference

of activities as adventure, leisure, historical, eco appreciation, urban life and

entertainments, or merely the joy of traveling, of all these affluent tourists.

Surprisingly three Asian countries are a part of this group. China, Japan and

South Korea nationals are high spenders on tourism activities. China, Japan and

South Korea must have some ethnic attachment with India. Buddhism can be a

strong ethnic link. Even the people, their habits, food and customs may have

common oriental touch. The best advantages being these countries are not far

away and are well connected by air.

Application of Factor Analysis

The researcher applied Factor Analysis based on Principal Component

Analysis on 34 variables of entrepreneurship that were found to be prominent

in the entrepreneurship literature. The objective was to find out if there were

any definite patterns in these variables and also establish the most dominating

factors that facilitated entrepreneurs operation. These variables were as

follows:

Entrepreneurial Abilities

• Business operating ability

• Risk taking ability

• Service recovery ability

• Profit making ability

• Trade knowledge level

• Social responsibility ability

• Quality consciousness

195

• Innovation ability

• Self-motivation level

• Customer relations ability

• Employee relations ability Venture performance

• Venture life span

• Venture success rate

• Product uniqueness

• Customized product

• Customer satisfaction

• Marketing thrust

• Tourism development

• Benefit to society

• Contribution to economic growth

• Professionalism in services

• Use of technology

• Training standards

Environment for entrepreneurship

• Post liberalization policies

• Government incentives

• Financial institutions aid

• Economic recession setback

• Industrial / commercial growth

• Tourism infrastructure

• Income level of tourism

• Tourism friendly culture

• Income level of tourists

• Civic facilities

• Law & order situation

• Availability of educated manpower

Data gathered on these variables were presented in the Likert scale of 1–

7, with 1 denoting least importance and 7 denoting most importance. The

information thus gathered was put to i) Kaiser – Meyer–Olkin Measure of

Sampling Adequacy and Bartlett’s test of Sphericity, ii) Catell’s Scree Plot iii)

196

Principal Component Analysis: Rotation Method: Varimax with Kaiser

Normalization. Statistical Process for Social Sciences (SPSS) software has

been used. The extracted result of the SPSS out put has been analyzed as per

the following report.

TABLE 4.47

KMO AND BARTLETT'S TEST

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.

.763

Bartlett's Test of Sphericity Approx. Chi-Square 1231.335

Df 231

Sig. .000


As presented in the Table 4.47, Kaiser-Meyer-Olkin measure of

sampling adequacy gives the output of .763. This according to Kaiser is

sufficient sampling adequacy for factor analysis. Anything above .500 can be

considered to be adequate. So, the sample size 200 is considered to be adequate

as per the KMO and Bartlett’s test. Bartlett’s test of sphericity to run the factor

analysis as it is significant at .000. Thus, anything less than 0.05 is mostly

considered in social science research as significant to reject the null

hypotheses. The variables are related to each other and it is worth applying

factor analysis to find out a definite pattern among them.

197

TABLE 4.48

COMMUNALITIES EXTRACTED BY PRINCIPAL

COMPONENT ANALYSIS

Initial Extraction

Risk taking ability 1.000 .487

Trade Knowledge level 1.000 .677

Innovation ability 1.000 .598

Venture success rate 1.000 .713

Product uniqueness 1.000 .570

Customer Satisfaction 1.000 .746

Marketing thrust 1.000 .750

Benefit to society 1.000 .513

Use of technology 1.000 .711

Training Standards 1.000 .700

Post Liberalization policies 1.000 .721

Government incentives 1.000 .667

Financial institutions aid 1.000 .655

Economic recession setback 1.000 .563

Industrial/commercial growth 1.000 .664

Tourism infrastructure 1.000 .725

Income level of tourists 1.000 .482

Tourism friendly culture 1.000 .479

Civic facilities 1.000 .610

Law and order situations 1.000 .580

Availability of educated manpower 1.000 .526

Profit making ability 1.000 .673

Extraction Method: Principal Component Analysis.

These 34 variables are put to factor analysis extraction method of

Principal Component Analysis. According to Kaiser Normalization,

communalities more than 1.000 is relevant. Thus, out of 34 variables, total 22

communalities are extracted, as demonstrated by Table 4.48. Thus, the above

mentioned extracted communalities are effective to throw light on

entrepreneurship. Communality shows how much of each variable is accounted

for by the underlying factor taken together. A high value of communality

198

means that not much of the variable is left over after whatever the factors

represent is taken into consideration.7

TABLE 4.49

STATEMENT OF TOTAL VARIANCE EXPLAINED OF

THE FACTORS EXTRACTED

Com- ponent

Total

Initial Eigen values

% of

Variance

Cumu-

lative

%

Total

Extraction Sums of Squared Loadings

% of

Variance

Cumu-

lative

%

Total

Rotation Sums of Squared Loadings

% of

Variance

Cumu-

lative

%

1 4.456 20.256 20.256 4.456 20.256 20.256 2.916 13.255 13.255

2 2.840 12.911 33.167 2.840 12.911 33.167 2.420 10.998 24.253

3 1.705 7.750 40.917 1.705 7.750 40.917 2.263 10.287 34.540

4 1.452 6.599 47.516 1.452 6.599 47.516 1.614 7.338 41.878

5 1.295 5.886 53.402 1.295 5.886 53.402 1.600 7.273 49.151

6 1.057 4.804 58.206 1.057 4.804 58.206 1.520 6.907 56.058

7 1.005 4.567 62.773 1.005 4.567 62.773 1.477 6.714 62.773

Extraction Method: Principal Component Analysis. Source: Primary Data.

Total variance shows (Table 4.49) that the initial Eigen values of 7

components being extracted. Principal Component Analysis extracted

components with Eigen values more than 1.000. It can be clearly seen the first

7 factors are responsible for a cumulative 62.773%. Thus majority of the total

Eigen values are covered by these 7 components. The first component has the

largest variance (20.256) from the mean and thus considered to be most

powerful. The second component has second largest variance from the mean

and thus second in value. And so further variances become less and less and the

value of corresponding components becomes less and less.

199

Diagram 4.1

Scree Plot

Component Number

21191715131197531

Eig

en

va

lue

5

4

3

2

1

0

Source: Primary Data

Cattel’s scree plot shows a reconfirmation of facts whether the

components are 7, or less or even more than that. The graph in Diagram 4.1 is

plotted with Eigen value and corresponding component number. It can be

clearly seen after the 7th component the scree falls freely. This denotes 8th

component onwards, till the last component can be rejected. The other fact to

be noted is components 1 to 7 have Eigen value 1 or more. 8th component

onwards the Eigen value is less than I.000. Thus, according to Kaiser all these

components (8 to 21 of the diagram) are to be rejected.

200

TABLE 4.50

ROTATED COMPONENT MATRIX OF

THE EXTRACTED SEVEN FACTORS

Name of the Factors Indicators of Entrepreneurship Factor

Loadings Cornbac Alpha

Factor-1(Venture

Success factor) Post Liberalization policies

.821

Venture success rate .811

Customer Satisfaction .671

Trade Knowledge level .590

Factor-2 (Business

Environment)

Civic facilities .731

Availability of educated manpower

.678

Tourism friendly culture .593

Government incentives .567

Factor-3 (Product

Development) Product uniqueness

.723

Innovation ability .702

Profit making ability .697

Factor-4 (Growth

opportunities) Marketing thrust

.682

Industrial/commercial growth .599

Law and order situations .555

Factor-5 (Tourism

venture scope) Tourism infrastructure

.805

Risk taking ability .524

Income level of tourists .523

Factor- 6 (Venture

planning) Economic recession setback

.662

Financial institutions aid .653

Benefit to society

Factor-7 (Training

and Development) Training Standads

.777

Use of technology .769

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in

10 iterations. Source: Primary Data.

Extraction method of Principal Component analysis has been applied to

rotation of varimax with Kaiser Normalization. The rotation was converged in

10 iterations using SPSS. The output as per Table 4.50 shows Rotated

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Component Matrix where 7 components each with few variables have been

extracted. The factor name selected fairly covers the bunch of variables shown

in the matrix. As the first component decided is Venture success factor as it

covers all the variables in component no. 1: Post liberalization policies,

Venture success rate, Customer Satisfaction, Trade knowledge level. Since

component no.1 has the highest variance and thus considered to be most

powerful, it has been selected as responsible for venture success. The same

procedure is followed for all the seven factors decided for the corresponding

seven components as follows:

• Venture success factor

• Business environment

• Product development

• Growth opportunities

• Tourism venture scope

• Venture planning

• Training and development

According to the factor analysis, these seven factors are most

responsible for the operation of entrepreneurial establishments.

The prominent variables with high loading are also identified following

Kaiser’s principle as:

• .500 to less than .500 – to be ignored

• .600 to .700 – poor

• .700 to .800 – moderate

• .800 to .900 – good

• More than .900 – excellent

202

The post liberalization policies .821, venture success rate .811, tourism

infrastructure .805 – all are considered good. The study can identify these as

the strongest indicators to bring in success. Similarly next in importance are

civic facilities .731, product uniqueness.723, training standards .777, use of

technology .769 – all are considered to be moderate. Factor analysis further

identifies the above mentioned indicators for effective venture management.

The extracted seven factors are subjected to correlation test to find out in what

way the factors were related to each other. The correlation table and the

interpretations are given below.

TABLE 4.51

MATRIX SHOWING CORRELATIONS BETWEEN

THE SELECTED SEVEN FACTORS Name of

the

Factor

F1 F2 F3 F4 F5 F6 F7

F1 1 .449(**) -.194(**) .248(**) .029 .253(**) .036

. .000 .006 .000 .685 .000 .613

200 200 200 200 200 200 200

F2 .449(**) 1 -.077 .371(**) .123 .314(**) .062

.000 . .280 .000 .082 .000 .382

200 200 200 200 200 200 200

F3 -.194(**) -.077 1 .191(**) -.034 .263(**) .203(**)

.006 .280 . .007 .630 .000 .004

200 200 200 200 200 200 200

F4 .248(**) .371(**) .191(**) 1 .113 .379(**) .132

.000 .000 .007 . .110 .000 .063

200 200 200 200 200 200 200

F5 .029 .123 -.034 .113 1 .016 -.037

.685 .082 .630 .110 . .826 .602

200 200 200 200 200 200 200

F6 .253(**) .314(**) .263(**) .379(**) .016 1 .194(**)

.000 .000 .000 .000 .826 . .006

200 200 200 200 200 200 200

F7 .036 .062 .203(**) .132 -.037 .194(**) 1

.613 .382 .004 .063 .602 .006 .

200 200 200 200 200 200 200

**Correlation is significant at the 0.01 level (2-tailed). Source: SPSS output of Primary Data.

203

The correlation Table 4.51 shows a matrix of all the seven factors. A

score of +1.0 denotes perfect positive correlation; score of -1.0 denotes perfect

negative correlation. Negative correlation means when one is more the other is

less and vice versa. A score of 0 denotes there is absolutely no correlation.

The seven factors are as follows:

• Venture success factor – F1

• Business environment – F2

• Product development – F3

• Growth opportunities – F4

• Tourism venture scope – F5

• Venture planning – F6

• Training and development – F7.

An attempt is made to find the relationship between the factors that

significantly constitute the entrepreneurial opportunities in tourism business.

Some of the relations are explained to express the overall reading of the

correlation table. The most notable feature is SPSS suggested significance level

of 0.01 as against the normal accepted value of 0.05; thus making the

correlations more specific. The result of two tailed correlation where two

results for each pair is given, thus both the scores are considered. The table also

shows the sample size as 200 for all the operations.

- Table shows correlation between F1 and F2-average positive (.449) one end and no relation (.000) at other end,

- Between F1and F3 – low negative (-194) one end and no relation (.006) at other end,

- Between F1 and F4 – low positive (.248) one end and no relation (.000) at the other end,

204

- Between F1 and F5 – very low positive (.029) one end and fairly high positive (.685) other end,

- Between F1 and F6 – low positive (.253) one end and no relation (.000) on other end,

- Between F1 and F7–very low positive (.036) one end and fairly high positive (.613) on other end. . Likewise the entire matrix can be examined for the correlation of a pair of factors at a time.

Examination of the table in the above mentioned procedure shows there

is not a single correlation where both the ends show no relation (using the set

significance level at 0.01). Thus the conclusion is all the seven extracted factors

are in some way or other connected to each other. Research result can be

confirmed as the extracted factors are all related to entrepreneurship and are

responsible for its success. Between one and another factor they are also related

as in turn they all relate to the source theme ‘Entrepreneurship’.

Association of the size of the entrepreneurial firm with the selected factors

It was also examined whether the extracted seven factors of

entrepreneurship vary with the size of the establishment. The following

hypothesis was used to achieve the objective.

H5: No significant difference exists between the size of the

entrepreneurial unit and the seven factors (Venture Success,

Business Environment, Product Development, Growth

Opportunities, Tourism venture scope, Venture planning and

Training & Development) influencing the attitude, ability,

performance, strategic thinking, and managerial decisions of

entrepreneurs.

205

It was attempted to find out whether the size of various tourism

establishments was responsible for making any difference in the seven factors

selected by factor analysis. The process adopted was to analyze the mean and

standard deviation of each factor against the three different sizes of the

establishment as small, medium, and large scale.

TABLE 4.52

STANDARD DEVIATION OF SEVEN FACTORS (F1 TO F7) SET

ACROSS THE ESTABLISHMENT SIZE

N Mean Std.

Deviation Maximum

F1 Small Scale 100 18.7700 4.62504 26.00

Medium Scale 79 17.7468 4.87923 25.00

Large Scale 21 18.4286 5.58186 25.00

Total 200 18.3300 4.83092 26.00

F2 Small Scale 100 19.7600 2.59806 24.00

Medium Scale 79 19.3671 3.17513 25.00

Large Scale 21 19.3333 2.74469 25.00

Total 200 19.5600 2.84727 25.00

F3 Small Scale 100 15.2100 3.25761 21.00

Medium Scale 79 15.5949 2.92434 20.00

Large Scale 21 15.6190 2.97449 20.00

Total 200 15.4050 3.09173 21.00

F4 Small Scale 100 14.9500 1.87689 18.00

Medium Scale 79 15.0253 2.34780 18.00

Large Scale 21 14.3810 2.45919 18.00

Total 200 14.9200 2.13457 18.00

F5 Small Scale 100 11.7200 2.04534 17.00

Medium Scale 79 11.8101 1.90193 16.00

Large Scale 21 11.7143 1.76473 15.00

Total 200 11.7550 1.95296 17.00

F6 Small Scale 100 15.2200 1.98774 19.00

Medium Scale 79 15.1646 2.27827 20.00

Large Scale 21 15.8095 1.91361 20.00

Total 200 15.2600 2.09867 20.00

F7 Small Scale 100 9.9200 1.34600 13.00

Medium Scale 79 9.8228 1.38453 13.00

Large Scale 21 10.0476 1.02353 12.00

Total 200 9.8950 1.32770 13.00

Source: SPSS output of Primary data

206

The standard deviation (Table 4.52) gives a clear picture of the fact that

the variance level decreases with every factor. The standard deviation of F1 is

the largest (for all firm sizes); standard deviation of F2 is second largest (for all

firm sizes) and so on to show standard deviation of F7 is the least (for all firm

sizes). So it is confirmed factor one (FI) is the strongest factor for

entrepreneurship as the variance is largest from the mean. The strength of the

factors gets reduced in descending order. This reconfirms that the factor

analysis test is correct where similar result is projected when FI, F2, F3, F4, F5,

F6, & F7 were extracted and the strength were also in descending order.

Apart from establishing the above mentioned fact, there are no other

visible patterns between the different sizes of the firms. That is the variance

from the mean of individual firm sizes are close to being equal. It is clearly

seen from the standard deviation and also from the maximum deviation

columns in every factor category the values of the firm sizes are almost equal.

There are no or insignificant difference of various sizes of entrepreneurial firms

as associated with the selected seven factors of entrepreneurship.

ANOVA test on selected factors and firm size groups

Subsequently, Analysis of Variance (ANOVA) was applied to test the

variance of the seven factors as related to the entrepreneurial firm sizes. Test

was applied to the firm size (small, medium, and large) in association with the

seven factors.

207

TABLE 4.53

ANOVA TABLE OF SEVEN SELECTED FACTORS AS ANALYZED

BETWEEN AND WITHIN FIRM SIZE GROUPS

The factors Sum of

Squares Df Mean

Square F Sig.

F1 Between Groups 46.430 2 23.215 .995 .372

Within Groups 4597.790 197 23.339

Total 4644.220 199

F2 Between Groups 8.019 2 4.009 .492 .612

Within Groups 1605.261 197 8.149

Total 1613.280 199

F3 Between Groups 7.615 2 3.807 .396 .674

Within Groups 1894.580 197 9.617

Total 1902.195 199

F4 Between Groups 7.068 2 3.534 .774 .463

Within Groups 899.652 197 4.567

Total 906.720 199

F5 Between Groups .397 2 .199 .052 .950

Within Groups 758.598 197 3.851

Total 758.995 199

F6 Between Groups 7.221 2 3.611 .818 .443

Within Groups 869.259 197 4.412

Total 876.480 199

F7 Between Groups .964 2 .482 .271 .763

Within Groups 349.831 197 1.776

Total 350.795 199

Source: SPSS output of Primary Data.

The ANOVA table 4.53 shows the sum of square (SS), degree of

freedom (df), Mean square (MS), F – ratio (F) and significance (Sig.). For the

present research the first column and the last column are relevant. It can be

clearly seen FI to F7 – all the seven factors have significance value much

higher than accepted set value of .050. The null hypothesis is not rejected.

Thus, in all the seven cases the null hypothesis of the variables is not related to

each other is not rejected. Test proves that there is no significant difference of

factors. It may be informed from the result of the one way ANOVA test that no

difference of opinions exist across the small, medium, and large entrepreneurs

208

on seven key factors that represent true scope for entrepreneurial opportunities

in tourism in the high tech city Bangalore.

Thus both the tables of standard deviation and the ANOVA conclusively

prove the fact – The size of the entrepreneurial firms is not in any way

responsible for altering the seven selected factors.

Entrepreneurs of allied activities demonstrating the seven factors

The seven factors were also present amongst the ‘allied activities

operators’. Secondary data provided sufficient inputs to identify these ‘allied

activities operators’ who were found operating with the seven factors as:

Venture Success, Business Environment, Product Development, Growth

Opportunities, Tourism venture scope, Venture planning and Training &

Development.

Here are some cases of innovative products of entrepreneurial

establishments of tourism and allied activities in Bangalore city:

� Anju Sudarshan's Theatre Café at Ranga Shankara a premier theatre hall

that attracts lot of tourists.

� Ms. Manjul Gupta's service to tourists through her health centre 'Body

Craft' a spa spread across four floors operating on Western and Oriental

styles of health care.

� Eagleton Golf village, a 500 acre golf village with 170 acres of golf

course, designed by Australia firm Pacific Gold Coast and promoted by

entrepreneur Arun Kumar to promote golf tourism. The complex house

209

resort, private villas, golf academy, clubhouse measuring 3 lakh sq. ft.

with restaurants, golf accessories shop and golf school.

� Levitate a tourists, artifact shop with souvenirs as rings, semi-precious

stones, bangles, beads, boutique shirts, skirts, belts, boxes, carry bags –

promoted by the entrepreneur Meghna Khanna, a MBA graduate who

gave up her corporate dreams to pursue her true calling.

� A number of painters and artists of Bangalore have sold their paintings

to hotels and restaurants. These paintings and murals adorn the lobbies,

banquet halls, dining halls, restaurants, bed rooms, corridors of the best

5 star hotels in Bangalore. The selected art galleries also attract a

number of tourists and city of art lovers. These artists and painters have

undoubtedly contributed to the cause of tourism and tourists are perhaps

their greatest admirer. The list of the art entrepreneurs include reputed

names as Paresh Hazra, Amitab Sengupta, Ravi Mandlik, Peter Hayman,

Henry salt, G. Gangatharan, Karunakaran, William Miller, R. Rowyer,

G. Adirekar, G. Shenoy, Kiran Mallapur, M.S. Murthy, Yusuf Arrakal

and Nambiar.8

� 'Bangalore Habba' the unique cultural festival that is performed by 2000

artists performing in almost 100 locations across the city over one month

promoted by two women entrepreneurs Nandini Alva and Padmini Ravi.

Both international and domestic tourists throng the city during

December to enjoy Bangalore Habba.

210

� Hansgrohe and Jaguar have ventured into innovative toilet and sanitary

fittings for 5 star hotels in Bangalore. The product range includes sensor

taps, Strass Swarovski, Indroform, fiber optic lighting, wall brackets and

crystal chandeliers. The entrepreneurs have also set up a number of

orientation camps to explain the usage of their products to architects and

interior decorators of hotels, motels and resorts, in Bangalore.

� Entrepreneurs venturing into the new concept of 'Tea Bar' in Bangalore

were found to be successful and highly demanded by the tourists.

Detailed report is narrated in the annexure chapter.

o Infinitea – English style tea bar promoted by Gaura Saria.

o My Tea House – A venture by tea-historian Anil Rawat serving

tea from different parts of the world.

o Some of the star hotels also started their own tea bars to

supplement the growing demand of the tourists in Bangalore.9

There were imposing shopping malls that were conceived and

successfully operated by entrepreneurs. Findings based on observation and

secondary data confirmed these malls provided the main attraction to urban

tourists as they housed state of art shops, restaurants, cinema halls, gaming

centers, beauty parlors, entertainment outlets – all that tourists need to spend

their time with, in the atmosphere of glamour, sophistication and excitement.

Findings are documented in details in the annexure section, of the following

malls:

211

1. Forum Mall – 100,000 sq.ft mall at Koramangala promoted by

entrepreneur Neeraj Duggal, the present vice president.

2. Bangalore Central (BC) Mall – 1,20,000 sq. ft. Mall promoted by the

Pantaloon Group, famous for ready-made garments.

3. EvaMall – Country's first mall to be exclusively dedicated to ladies.

4. Garuda Mall – spread over 75,000 sq.m with parking facility for over

1000 cars, the mall is promoted by entrepreneur Uday Garudachar.

5. GopalanMall- has 2,38,000 sq.ft. of retail space, situated on Mysore

Road a popular venture by entrepreneur Dinesh Malpani, CEO of the

jubilant group that launched the Gopalan Mall.

6. Lido Mall – situated on the famous land mark of the familiar Lido

Theatre which actually gave away place for the mall, promoted by the

original owners who thought Mall business was a better option.10

• Entrepreneurs in Bangalore ventured into amusement Parks, as the state

government offered incentive by reducing entertainment tax from 20%

to 10% and were considering a request for further reduction to 5%. The

detailed report on, Wonder La, the best and most popular amusement

Park off Mysore Road at Hejjala, promoted by entrepreneurs

Kochouseph Chittilappily, the present managing director of Wonder La

Holidays Pvt. Ltd. is documented in annexure section.

• Entrepreneurship in Hotel Management software was also quite

prominent in the IT City. Press release extract of one such enterprenuer,

Vishnu Murali Konduru the venturer of Saastra Software as a service for

212

tourism transportation and accommodation, has been documented in the

annexure section.

There were considerable amount of entrepreneurship enterprises on

health therapies and fitness centers, scattered all over the city, catering to

the needs of the health conscious globe-trotting tourists, the domestic

visitors and the mobile ITprofessionals. Extracts of the published report

are presented at annexure.

1) TaiChiAcademy- imparts Chinese martial art for tourists. Tai Chi

teaches exercise movements for physical fitness centers are at

Bangalore Palace Grounds, Lourd Vijay's DanceSchool, Active Canvas

Studio, and at Alliance Francaise

2) Yoga Centers- There are various centers as Sudarshan Kriya at the Art

of Living, Siddha Samadhi Yoga, Power Yoga, B.K.S. Iyengar style of

yoga, artistic yoga, Ashtanga Yoga from the teaching of Pattabhi Jois

and Hatha yoga for the spiritually inclined. Report of Rupa Satyam

who rums one of the most popular yoga center have been documented

in the annexure section.

3) 27 years old therapist entrepreneur Sheela Bajaj practices and teaches

meditation. Besides being a chakra and reiki healer, she is also a gem

and crystal therapist. Sheela Bajaj's interview with the media has being

documented in the annexure section.

4) The premier names practicing Chakra therapy, gemology and reiki in

Bangalore include Indira Bhangar, Arnav Medhi and Pam Mehra.

213

Published interview with Arnav Medhi revealed that the later was a

typical MBA till he decided that he wanted out the rat race and become

an entrepreneur in pranic and spiritual healing.

REFERENCES

1) Drucker Peter F. (1985) ‘Innovation and Entrepreneurship – Practice and Principles’. Harper Row Publishers. New York.

2) J. Schumpter (1934) ‘The Theory of Economic Development’. Cambridge Mass: Harvard University Press.

3) Rao Smitha ‘Tourism plans go full throttle’. The Times of India, Bangalore. Jan 11, 2007.

4) United Nations World Tourism Organization Statistics 2007.

5) Ibid.

6) Ibid.

7) Kothari C.R.(2009) Research Methodology, New Age International Pvt. Ltd. publishers. New Delhi.

8) Mendonca Allen. 'Arty facts." India Today. Simply Bangalore September 2007 Vol. 3 Number 8: New Delhi. Pg. 9.

9) Mehra Neeti. 'Blazing the Coffee trail.' Express Hospitality September 1-15, 2006. Pg. 22.

10) Govindarajan Nirmala. 'City In Al League.' The Times of India, Bangalore. Tuesday, October 2, 2007.

chapter iv profile of entrepreneurs and their...

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