TOURISM BUSINESS AND LIVELIHOOD OUTCOMES OF HOST PEOPLE IN SOUTHWESTERN NIGERIA

 

K. Oyebisi BAKARE

Department of Family, Nutrition and Consumer Sciences, Faculty of Agriculture, Obafemi Awolowo University, Ile-Ife, Nigeria

 

 

 Abstract

The study examined the influence of tourism business on livelihood outcomes in Southwestern Nigeria. The study employed survey research design with the use of primary data. The study was carried out in the twelve host communities of  six states (Ekiti - Ikogosi Warm Spring and Ipole – Iporo Water-falls; Lagos - Onikan Museum and Whispering Palms Resorts in Badagry; Ogun - Adire Market in Itoku and Olumo Rock; Ondo - Idanre Hills and Oke-Maria; Osun - Olumirin Waterfalls in Erin – Ijesa and Osun Osogbo Shrine; and Oyo - Oyo National Park and University of Ibadan Zoological Garden. The sample for the study consisted of 784 business owners selected using inclusion criteria of residence around tourism sites, age not less than 18 years, and engagement in business in and around tourism destinations. The results of regression analysis on tourism business and livelihood outcomes revealed coefficients of multiple determinations of income (R² = 0.816, f = 22.5); food security (R² = 0.729, f = 19.7); and reduced vulnerability (R² = 0.603, f = 31.4) indicating prediction of 82%, 73%, and 60% respectively of the variations in the study. Based on the findings, the study concluded that tourism availed business opportunities in the rural areas and contributed considerably to livelihood outcomes such as increased income, food security, and reduced vulnerability for the host people.        

    Keywords: Tourism business, Income, Food security, Reduced vulnerability, Small business, Entrepreneurship, Livelihoods.

 

 

INTRODUCTION

         Livelihood is often synonymous with life itself. The degree of fulfilling both material and experiential needs is crucial to living hence; it is a major concern for most societies, nations, and the world at large. Livelihoods are not simply a localized phenomenon, but connected by environmental, economic, political and cultural process to wider national, regional and global arenas. Individuals often engage in varying job and business endeavours to earn living that will translate to food security and income generation to cope with stress, shocks, and emergencies that may arise at any point in time (Bakare, 2016). The sustainable livelihoods framework (SLF) helps in thinking holistically about the things that poor might be very vulnerable to, the assets and resources that help them thrive and survive, and the policies and institutions that impact on their livelihoods (DFID, 1999).  The framework shows how, in differing contexts, sustainable livelihoods are achieved through access to a range of assets which are combined in the pursuit of different livelihood strategies. The livelihood outcomes that appear in the generic framework include; more income (cash); increased well being (awareness of self, wellbeing); reduced vulnerability (how better they are resilient as a result of  increase in livelihood assets); improved food security (increased financial capital to buy food); natural resource sustainability (ownership of land based property), with cognizance to socio business characteristics.

          It has generally been established that, 60-70% of rural dwellers in Nigeria and other developing countries in the Global South who depend on agriculture as their source of sustenance are living in absolute poverty (Kolawole & Torimiro, 2006). To be precise 70.2 % of Nigerians live below the poverty line (World Bank, 2006).  It was also observed that the share of people living in poverty is larger in Africa than any other region in the world (Gasu, 2013). Furthermore, Oyesiku (2009) emphasized that 52% of sub-Sahara Africa’s population was poor in 1985, which rose to 63% in 1990 and was estimated at 63.5% in 2009). It was finally concluded by World Bank (2006) that poverty is a rural phenomenon.

          A good working definition of livelihood is provided by Ellis (2000) “the assets (natural, physical, human, financial and social capital), the activities, and the access to these (mediated by institutions and social relations) that together determine the living gained by individual or household” (livelihood outcomes). These livelihood outcomes often manifest in terms of food security, income, and reduced vulnerability with interdependence on personal socio business variables (Bakare, 2016). Livelihood outcomes in form of achievement of livelihood strategies such as more income, increased well being, reduced vulnerability and improved food security obtainable from participation in non-farm work exerts a positive and statistically significant effect on household income and food security status (Shahbaz, 2008).  

            Odeleye and Oyekanmi (2013) alluded that that tourism and rural development are of paramount importance in order to achieve the much needed economic diversification as a way out of the current global economic meltdown. It was suggested that government should leverage private sector involvement in providing requisite infrastructure in selected tourist areas in the country. Due to numerous economic benefits of tourism and its potential growth it helps in the increase of standard of living of the people by offering new and better jobs, which in terms helps them to improve the quality of life and their families (Zaei & Zaei, 2013). The traits of creativity, risk-taking, innovation, strategic thinking and constructive engagement against the government by discontented Nigerians could as well be directed to entrepreneurship development (Anyadike, Emeh - Ikechukwu, & Ukah, 2012). Olowookere and Elegbeleye (2014) submitted that entrepreneurship serves as a guarantee for sustainable development of any economy. Igwe, Adebayo, Olakanmi, Ogbonna and Aina (2013) reported that the National Institute for Social Research (NISER) and the World Bank revealed Nigeria’s unemployment rate to involve over 55% of her working population. Given the immense socio-economic contributions of entrepreneurship, the small business sector is highly recognised as increasingly the main profitable source of all financial houses (Agyapong, Agyapong & Darfor, 2011). With the current rate of unemployment and poverty level in Nigeria, Bakare (2016) adduced that small business has been recommended via research as the only source of livelihood to millions of Nigerians, more importantly tourism based business in the rural areas. Agbenyagah (2013) averred that small business sector is a major role-player in various economies world-wide. About 60% of all the business established in Nigeria is on small scale level (Okeke, Ezenwafor, & Femiwole, 2013). It is against this fact that tourism business is alternated to mean small business as it has with it all the attributes spelt out by Alaye-Ogan (2012) - a small business as companies with capital base between twenty thousand naira and thirty million naira (equivalent of $125 to $193,500), Hatten (2012) - a company is considered small if it is independently owned, operated, and financed; has fewer than 100 employees; and has relatively little impact on its industry. The Central Bank of Nigeria (2014) defined small and medium enterprise (SMEs) as business with asset base of between five thousand and five-hundred million naira, and staff strength of between 1 and 300 people. Financial decision-making is of utmost significance to small businesses (Marx, De Swardt, Beaumont-Smith, & Erasmus, 2010). At the same time, empirical research outcomes indicate that roughly 30% of the owner-managers lack skills including business skills (Roodt, 2005). According to Ligthelm and Van Wyk (2004), owner-managers of small businesses lack relevant skills such as financial acumen and accounting, information technology and business skills. There are several factors that limit the performance and success of small businesses. These factors are interdependent and on most occasions, are equally related to each other.  Alarape (2010) adduced non encouraging situation of small business in Nigeria to inadequate infrastructure, poor access to funds and implementation of policies, restricted market access, overbearing regulatory and operational environment.

        Improving food security of rural households requires integrated development interventions aimed at improved natural resources management and diversification of livelihood strategies including interventions to create non-farm employment opportunities. On the other hand, due to shortage of startup capital, limited skills, weak marketing systems and inadequate policy attention, employment opportunities in non-farm or off-farm activities are extremely rare in rural African communities (Gebrehiwot & Fekadu, 2012).            Bazezew, Bewket, and Nicolau (2013) adduced that food insecurity is a chronic problem in that, on average, households consume from own production for only about six months and reported negative and significant correlation between family size and household incomes. Improving food security of rural households requires integrated development interventions aimed at improved natural resources management and diversification of livelihood strategies including interventions to create non-farm employment opportunities

           Mthembu (2012) employed survey approach in his study found that largest percentages of people agree that tourism development can contribute positively to the creation of job opportunities, development of entrepreneurial skills and the generation of increased income. However, the mentioned outcomes may or may not be relevant in any given situation. The main difficulty with this part is that the livelihood outcomes are not always consistent but surely incommensurable. For example, it is not easy to measure the relative values of increased well being as compared to increased income. Most tourism and small business literature concentrate on the financial problems of small scale businesses (Adisa, 2008), but the study concentrate on livelihood potentials of tourism business by taking cognizance of increased income, food security, and reduced vulnerability. The study attempted to make important addition to the existing literature by investigating livelihood outcomes in the context of the sustainable rural livelihoods framework and by taking into account the opportunities inherent in tourism resources which abound naturally mostly in less advantaged, rural communities that are generally tourism endowed.

Objectives of the study

  1. indentify  the socio-economic characteristics of tourism host people
  2. assess the contribution of tourism business to livelihood outcomes in the host communities

Hypothesis

  1. There is no significant relationship between tourism business and rural livelihood outcomes.

Methodology

         The study was carried out in Southwestern Nigeria comprising six states: Osun, Oyo, Ondo, Ondo, Ekiti, Lagos and Ogun. The study adopted a descriptive survey research design. The study relied on primary data, using interview guided questionnaire that was author-designed. The tourist sites selected for the study included: Ikogosi Warm Spring and Ipole – Iporo Water-falls (Ekiti); Onikan Museum and Whispering Palms Resorts in Badagry (Lagos); Adire Market in Itoku and Olumo Rock (Ogun); Idanre Hills and Oke-Maria (Ondo); Olumirin Waterfalls in Erin – Ijesa and Osun Osogbo Shrine (Osun); and Oyo National Park and University of Ibadan Zooological Garden (Oyo). Two destinations were selected from each state of six (6) states in Southwestern Nigeria using purposive sampling techniques, bearing in mind the rurality of the neighborhood and functionality of the attractions.  

        The population for the study was adult rural dwellers in and around host communities in the Southwestern Nigeria. Inclusion criteria was employed to select 784 respondents included; age 18 years and above, residence within and around the tourism destination, and engagement in businesses in and around tourism sites. Livelihood outcomes were measured using three indices of income, food security, and reduced vulnerability on 4-point Likert scale ranging from Strongly Agreed (4) to Strongly Disagreed (1). A four point modified Likert scale was used, which ranged from Sustainable (5), Fairly Sustainable (3), Low Sustainability (1), and Not Sustainable (0), to collect information on rural livelihood capitals. The reliability of the instrument was achieved through a test-retest method of two weeks interval. The draft of the questionnaire was given to four (4) experts in psychometrics for validation and necessary suggestions. The reliability test gave Cronbach’s Alpha (α) ranging from 0.66 to 0.81.

            Regression analysis was used to test the hypothesis. Explanatory variables for the regression modeling included selected personal and business characteristics that are assumed to influence livelihood outcomes of respondents in the study area. Rural livelihood outcomes are generally influenced through tourism business by a range of personal factors and business characteristics.

 

RESULTS AND DISCUSSION

Table 1:  Personal Characteristics of Respondents

Characteristics

Variable Descriptions

Freq. (n=784)

%

Age

18-30 years

31-60 years

60 years and above

197

463

124

25.13

59.06

15.82

Sex

Male

Female

316

468

40.31

59.59

Level of education

No formal education

Primary education

Secondary education

Tertiary education

139

241

247

157

17.73

30.74

31.51

20.03

Marital status

Single

Married

Others

231

451

102

29.46

57.53

13.01

Age of Business

Less than 2 years

2-5 years

Above 5years

635

127

22

80.99

15.20

2.81

Number of people involved

in the business

Self (1)

2-5

6-10

11-50

511

203

57

13

65.17

25.89

7.27

1.66

Income per month

Less than ₦5,000

₦5,000-₦20,000

₦21,000-₦50,000

₦51,000-₦100,000

Above ₦100,000

115

153

282

133

101

14.67

19.52

35.97

16.96

12.88

Source of start up capital

Family

Friends

Personal saving

Loan

Credit facility

122

34

511

84

33

15.56

 4.34

65.18

10.71

  4.21

Business Focus

Trading

Service Rendering

Production

Value addition

463

197

73

51

59.91

25.13

  9.31

  6.51

Number of people involved

in the business

Self (1)

2-5

6-10

11-50

511

203

57

13

65.17

25.89

  7.27

  1.66

Business inspiration

Media

Family / Friends

Parents

Government

School

113

255

221

124

71

14.41

32.53

28.19

15.82

  9.06

Entrepreneurship training ever attended

None

NGO

LG

SG

FG

Individual/Politician

Club

Cooperatives

514

43

62

14

00

16

31

104

65.56

 5.48

 7.91

 1.76

    00

 2.04

 3.95

13.27

Money / Loan ever received

 

 

 

 

 

None

NGO

LG

SG

FG

Individual

Club

Cooperatives

Family/friends

293

82

23

11

9

67

34

204

61

37.37

10.46

 2.93

 1.40

 1.15

 8.55

 4.34

26.02

  7.78

         

Field Study, 2015.

 

Personal Characteristics of Respondents

          Table 1 showed the personal characteristics of respondents. It showed that a little above half (59.06%) of the respondents falls between 31 and 60 years of age which fall within the vibrant active years of life. One quarter (25.13%) of the respondents fall within 18 and 30 years of age while only 15.82% were old people from 60 years and above engaging in one business or the other around tourism areas. Quite above half (59.59%) of the respondents was female while the remaining 40.41% were males. The results on table 1 also indicated the distribution frequency of the educational background of the respondents who participated in the study. It showed that 17.73% of the respondents had no formal education, about one third (30.74%) of the respondents had primary education, 31.51% had ever attended secondary school, while one fifth (20.03%) of the respondents had tertiary education being anything above secondary education. From the results, it can be deduced that the tourism destination is habitable and conducive for different people irrespective of their educational background. The marital status of the respondents as indicated on the table was single (29.46%), more than half of the respondents being represented by 57.53%  were married, while others (13.01%) were regarded as divorced, separated or widowed.

          The income of respondents monthly revealed that 14.67% being represented by 115 respondents had less than ₦7,500.00 average incomes per month. This implies that only about 1/6th of the respondents earned less than minimum wage of ₦7,500.00 per month with engagement in tourism based businesses. About 36% of the respondents earned between ₦21,000 and ₦50,000 per month, another 16.96% earned between ₦51, 000 and ₦100,000 per month, while the remaining 12.88% representing 101 respondents earned above ₦100,000 per month. The start-up capital for engaging in tourism business by the respondents showed that 122 representing 15.56% had their financial support from family, 34 respondents being represented by 4.34% had support from friends. Majority (511) of respondents representing 65.18% secured financial aid for business from their personal savings. Eighty-four of the respondents representing 10.71% had their start-up capital from loans while 33 of respondents (4.21%) had their business capital from credit facility. The business focus of respondents showed that trading activities with 463 respondents representing 59.91% involved in buying and selling around tourism destinations while a quarter (25.13%) of the respondents were involved in service rendering which includes hair making, shoe repairing, tour guiding, entertainments, and hoteling among others. While 6.51% of the respondents were involved in value addition, only 9.31% were involved in production of one good or the other.

         Age of business or number of years engaged in business around tourism destinations showed that 635 respondents representing 80.99% had been in business for less than 2 years, 15.20% of the respondents had been in business for 2 to 5 years while only 22 respondents representing 2.81% had been in business for over 5 years. The implication is that tourism business is serving as a panacea for the increasing unemployment rate. People around tourism attractions are taking advantage of the emerging tourism in their locality to earn a living for themselves. Number of people engaged in business showed that over half (65.17%) of the respondents were solely involved in their business. This means that they did not employ staff from the family or community to partake in business. Only 25.89% of the respondents had two to five people including self involved in their business and another 7.27% of respondents had between 6 and 10 staff including self employed in their business. While 13 respondents representing 1.66% had between 11 and 50 staff including self in their businesses.            Business inspiration of respondents revealed that 255 representing 32.53% got business inspiration from family and friends, 28.19% got their own business inspiration from parents, 14.41% were inspired to business by media including both prints and non prints, and 15.82% were inspired by government interventions and programmes. While 9.06% of the respondents were inspired by school / education or the type of exposition they had via their course of study or discipline.  Over one third (37.37%) of the respondents had never obtained loan from any quarters. Only 10.46% got loan or monetary aids from NGOs, 26.02% had ever got loan from cooperatives, 2.93% got loan from Local Government, and one quarter (26.02%) of the respondents got loan from cooperatives. Another 1.15% of the respondents got loans federal government, while state governments issued loans to 1.40%.

Table 2: Regression analysis of tourism business and livelihood outcomes (Income)

Variable description

Unstandardized Coefficients

Standardized Coefficients

t-value

P value

B

Std. Error

Beta

(Constant)

19.759

1.660

 

11.904

.000

Age

0.233

0.503

0.096

0.464

.646 (NS)

Sex

0.171

0.677

0.041

0.253

0.802 (NS)

Marital status

-0.244

0.346

-0.152

-0.704

0.486 (S)

No of dependants

-0.536

0.314

-0.279

-1.708

0.097 (S)

Age of business

0.936

0.720

0.217

1.302

0.201 (S)

Educational level

0.171

0.677

0.041

0.253

0.802 (NS)

Entrep. Inspiration

0.152

0.032

0.176

1.027

0.585 (NS)

Access to capital/credits

1.115

0.680  

0.271

1.640

0.111 (S)

Business focus

1.114

0.669  

0.231

1.639

0.111 (S)

No of people involved in business

-0.252

0.232

-0.176

-1.088

0.285 (NS)

Entrep training

-0.151

0.061

-0.312

-2.489

0.004(S)

S – significant; NS - not significant; F = 22.5; df (11, 772); p < 0.001; r = 0.912; R2 = 0.832.

Field Study, 2015.

Tourism Business and Income - Table 2 showed the regression analysis of significant relationship between tourism business and livelihood outcomes (income). The results revealed that there were associations between independent variables (marital status, number of dependants, age of business, and access to credits, business focus, and entrepreneurship training. However, there were no associations between some independent variables (age, sex, educational level, entrepreneurship inspiration, and number of people involved in business). Marital status (t = -0.708; p 0.486) was negatively associated with income. An increase in the number of years of business (t = 1.302; p = 0.201).  Access to capital showed positive and significant correlation with average monthly income (t = 1.640; p = 0.111). This implies that as capital availability increases by one unit, average monthly income increases by a factor of 0.271. The finding of the results has corroboration with the findings of Mthembu (2012). Business focus (t =-1.639, p=0.111) was positively and significantly correlated with income which is one of the major elements of livelihood outcome.  Other variables held constant, the type of business, product (tangible) or service (intangible) increases respondents’ incomes by a factor of 0.231. The judgment for this may be adduced to the fact that some products are portable while services are extremely immobile. Entrepreneurship training was found to be associated with livelihood outcomes (income) of respondents in the rural area. It was found that entrepreneurship training increases average monthly income by a factor of 0.312. This result was consistent with the findings of Bazezew et al (2013) who reported negative and significant correlation between family size and household incomes. The findings also revealed the significant relationship between tourism business and livelihood outcomes; income (r = 0.912; p<0.001).  The maximum likelihood estimates of the multiple regression model showed that marital status, number of dependants, age of business, access to capital, and business focus, and entrepreneurship training were the important factors influencing average monthly income of respondents, and thus their livelihood outcomes. The finding is in agreement with Zaei and Zaei (2013). The coefficient of multiple determinations is 0.816, indicating that about 82% of the variation in total annual income of the sampled host people was captured by the model while the f-ratio is 22.5 significant at 0.0.5. From the table, tourism business as a variable captured influence of engagement on respondent’s average monthly income.

Table 3: Regression Analysis of Tourism Business and Food Security

Variable description

Unstandardized Coefficients

Standardized Coefficients

t-value

P value

B

Std. Error

Beta

(Constant)

14.303

2.326

 

      6.150

  0.000

Age

1.689

0.623

0.294

      2.710

0.008(S)

Sex

1.182

0.314

0.514

      1.106

0.629(NS)

Marital status

0.780

0.703

0.164

 1.109

0.271(S)

No. of dependants

-0.071

0.269

-0.030

-0.263

0.793(NS)

Age of business

0.340

0.534

0.184

  0.636

0.127(S)

Educational level

-0.044

0.132

-0.031

-0.331

0.741(NS)

Entrep. Inspiration

1.132

0.417

0.164

0.246

0.613(NS)

Access to credits

-0.793

1.235

-0.275

  -0.642

0.223(S)

Business focus

0.189

0.261

0.093

  0.722

0.473(S)

No of people involved in business

2.801

0.084

0.010

      0.335

0.738(NS)

Entrep training

0.600

0.774

0.095

  0.775

0.441(S)

S -significant at 0.05; NS - not significant; F=19.7; df(11, 772); p<0.001; r=0.743; R2=0.552.

Field Study, 2015.

 

Tourism Business and Food Security - From Table 3, the results of regression analysis identified age (t = 2.710, P=0.008), marital status (t =1.109; p= 0.271), age of business (t = 0.636, P=0.127), access to credits (t = -0.642, P=0.223), business focus (t = 0.772, P=0.473) and entrepreneurship training (t = 0.775, p=0.441) and tourism business as significant determinants of food security of the respondents. The coefficient of multiple determination is 0.729, indicating that about 73% of the variation in food security of the respondents was captured by the model with f-ratio of 19.7 at 0.05 significant level. From the table, tourism business as a variable captured influence of engagement on respondent’s food security. The findings also revealed the significant relationship between tourism business and food security (r = 0.743; p<0.005). It was found that respondents in tourism sites earned more income and were able to secure food better than those in the tourism neighborhoods. The reason for this is not far-fetched as they will sell more and earn more than their counterparts in the neighborhoods and be able to expend enough money on food. An increase in the number years of business increases the demonstration of food security by a factor of 0.184. The older the business the better the acumen gathered from operations over the years whether in a hard way or otherwise. Access to credits showed positive and significant correlation with food security (t =0.642, P=0.223). As credits access availability increases by one unit, the means of procuring food will increase by 0.275, thereby aiding food affordability. The result is in agreement with Bakare (2016) that stated that outcomes are also determined by the types of assets people have which maybe in terms of their socio-economic characteristics. This is in agreement with (Shahbaz, 2008 that averred that participation in non-farm work exerts a positive and statistically significant effect on household income and food security status.

Table 4: Regression analysis of tourism business and reduced vulnerability

Variable description

Unstandardized Coefficients

Standardized Coefficients

t-value

P value

B

Std. Error

Beta

(Constant)

16.811

1.370

 

12.268

0.000

Age

1.363

0.481

0.252

2.834

0.005(S)

Sex

0.654

0.428

0.184

1.528

0.129(S)

Marital status

-0.172

0.288

-0.054

-0.598

0.551(S)

No of dependants

0.000

0.342

0.000

-0.001

0.999(NS)

Age of business

1.025

0.520

0.179

1.972

0.051(S)

Educational level

0.213

0.201

0.267

   1.014

0.011(S)

Entrep. Inspiration

0.321

0.131

0.136

   1.031

0.021(S)

Access to credits

0.773

0.631

0.179

1.226

0.224(S)

Business focus

0.340

0.534

0.084

0.636

0.127(S)

No of people involved in business operation

-0.151

0.178

-0.080

-0.846

0.399(S)

Entrepreneurship training

0.059

0.667

0.008

0.088

0.930(NS)

S - significant at 0.05; NS - not significant; F = 31.4; df (11, 772); p < 0.005; r = 0.777; R2 = 0.603.

Tourism Business and Reduced Vulnerability - From table 4, Linear regression analysis identified age (t = 2.834; p=0.005), sex (t = 1.528; P=0.129),  marital status (t = -0.598; , p=0.551), age of business (t = 1.972; p=0.051), educational level (t = 1.014;p=0.011), entrepreneurship inspiration (t = 1.031; p=0.021) and access to credits (t = 1.226; p=0.224), business focus (t = 0.636; p=0.127, number of people involved in business (t = -0.846; p=0.399) and tourism business as significant determinants of reduced vulnerability of the respondents. Reduced vulnerability of rural dwellers in the study area requires improving some socio economic characteristics of rural dwellers. Interventions aimed at improved livelihood strategies for diversification for improved livelihoods including engagement in businesses that arise from tourism events in the rural areas need to take cognizance of the significant factors predicting tourism business.

The coefficient of multiple determination is 0.603, indicating that about 60% of the variation in reduced vulnerability of the respondents was captured by the mode with f-ratio of 31.4 at 0.05 significant level. The findings also revealed the significant relationship between tourism business and reduced vulnerability (r = 0.777; p<0.001). The implication is that an increase in the level of educational background of respondents increases the experience of reduced vulnerability by a factor of 0.267. The older the business the more the ideas and understandings of the business strategies to reduce the incidence of vulnerability. Access to credit showed positive and significant association with reduced vulnerability. As credit access increases, the respondents were less prone to vulnerability. The finding is at variance with Ligthelm and Van Wyk (2004) that owner-managers of small businesses lack relevant skills such as financial acumen and accounting, information technology and business skills.

 

Conclusion

        The objective of the study was to contribute knowledge to the discussion on influence of tourism oriented business on host people in Southwestern Nigeria. The study indicated that tourism resources in the host communities which are mostly rural areas created linkages between the personal socio business characteristics of the individuals in the host communities. There was positive implication for business creation which further translated to livelihood outcomes. The study revealed that the personal socio business factors were significant to seizing opportunities in tourism business for livelihood outcomes among host people. It was observed in the study that tourism availed business opportunities in the rural areas and was a vital component of host community livelihoods. A good number of business trickled from tourism affiliations of the host communities. It was discovered that these businesses contribute considerably to livelihood outcomes such as increased income, food security, and reduced vulnerability considering personal socio business characteristics. The fact that tourism entrepreneurs were mostly residents contributed significantly to the sustainability of rural and small communities by pulling patrons from the teaming urban and city population towards host communities. The characteristics of host people were found to influence their involvement in tourism oriented businesses. The significance of attractions in rural areas cannot be over-emphasised as it formed the major pull factor for crowd (tourists) who constitute patrons for products of innovation by the host people. It was obvious in the study that rural dwellers were benefiting from tourism on the basis of job creation and income generation. It would be difficult for Nigeria to attack its poverty myriad unless it takes advantage of tourism development for peoples livelihoods especially in the rural areas which are mostly blessed with scenic assets. If people have social and economic infrastructure, the height of crimes and hunger will lessen and tranquility will be experienced all over. 

         Thus, the study has practical significance for designing a more targeted and effective livelihood outcome (income, food security, and reduced vulnerability) generated related development interventions in the study area, and in other similar environments in the country. For effective and sustainable livelihood outcomes in the host communities, there is need for governments to embark on training and infrastructural development programmes that will improve the personal socio economic characteristics of the people. Strengthening both formal and informal education (vocational training) should have to be promoted to increase rural participation in more viable livelihood options and offer better prospects for improving livelihoods.

 

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