Factors influencing the establishment of agro tourism centres: A logistic regression approach

Introduction

Agritourism is the incorporation of tourism with agriculture. It promotes agriculture and allied activities as a tourism product. Agri-tourism is a rural enterprise which incorporates an operational farm along with a commercial tourism element. Agro-tourism can be considered as a dominant diversification option for sustaining viability of the agricultural sector. Agro tourism not only benefit the farmers but mutually benefit the society. It creates employment to the rural people, preserves agricultural traditions and heritage, promote local food systems and enables tourists to learn the sustainable farming methods. Overall Agro tourism promotes the socio-economics and sustainable development. Agritourism is increasingly recognized as an important strategy that can contribute to agricultural development through diversification of farming activities. At present, agritourism is promoted by most of the countries in the world aiming at sustainable rural development. Further, agritourism can also be explained as a holiday concept of visiting an agribusiness operation for the purpose of enjoyment, education or involvement in the activities of the operation. However, the establishment of Agro tourism centres is influenced by several socio-economic, infrastructural, financial, and institutional factors, which vary across regions and among entrepreneurs.

The decision to establish an Agro tourism centre is not solely determined by the availability of agricultural land or farm, but also depends on factors such as the farmer's education, farming experience, landholding size, income, accessibility, availability of amenities, investment capacity, entrepreneurial skills, and proximity to tourist attractions. Understanding these factors is essential to identify the key drivers and barriers affecting the establishment of Agro tourism enterprises. Such knowledge helps explain why some farmers successfully diversify into Agro tourism while others continue to rely exclusively on conventional farming. Therefore, analysing the factors influencing the establishment of Agro tourism centres is crucial for developing effective policies and support mechanisms to promote this enterprise. The findings provide valuable insights for policymakers, extension agencies, financial institutions and prospective entrepreneurs in designing location-specific strategies, improving rural infrastructure, facilitating access to finance, and strengthening entrepreneurial capacity.

Materials and Method

The present study was based on primary data collected from 90 Agro tourism centre (ATC) owners and 90 non-ATC farmers from Goa and the Konkan region of Maharashtra. In the Konkan region, 60 ATC owners and 60 non-ATC farmers were randomly selected from the five districts of Sindhudurg, Ratnagiri, Raigad, Thane, and Palghar, while in Goa, 30 ATC owners and 30 non-ATC farmers were randomly selected from the two districts, namely North Goa and South Goa. Thus, a total of 180 respondents were selected for the study and the required data were collected through the survey method using a pre-tested structured questionnaire

Analytical tools

To understand the factors influencing establishment of Agro tourism centres, logistic regression analysis was carried out as given below:

Logistic regression analysis

Logistic regression (LR) is a statistical analysis tool for modelling the relationship between a response variable and a set of explanatory variables when the response variable is categorical. Logistic regression does not have the requirements for the independent variables to be normally distributed, linearly related or of equal variance within each group. The establishment of an ATC is a discrete choice outcome i.e dependent variable is dichotomous therefore; logistic regression is appropriate as it estimates the probability of occurrence of a binary event based on a set of explanatory variables. A total of fourteen explanatory variables were included in the model based on review of literature, field observations and logical relevance to Agro tourism development:

Y= whether farmer is an ATC entrepreneur or not If Yes=1, if No=0

Xi are independent variables: X 1 = Age (years) X 2 = Education level X 3 = Annual Income from farm business (Rs.) X 4 = Income from off farm business (Rs.) X 5 = Distance from main Road (Km) X 6 = Farming Experience (years) X 7 = Land holding size (ha) X 8 = Distance from nearby tourism spot (km) X 9 = Labour availability X 10= Available amenities X 11 = Green technology adoption X 12 = Electricity supply issue X 13 = startup capital X 14 = % area under plantation crops In order to predict the probability of the dependent variable and to apply logistic transformation, the probability function can be written as Equation 1, where p represent the probability of occurrence of an event and 1-p is the probability of non-occurrence of an event.

The logit transformation equation

After logit transformation is applied the equation becomes;

After applying the logit transformation, we derive an equation expressing the relationship in term of predictor variable and coefficients. By solving this transformed equation, we arrived at the logistic regression (LR) model which predict the probability of Y occurring as given in equation 4.

Where, P(Y) = probability of Y occurring; e is the base of natural logarithm and β0 represents exposure variable or constant, β1…n are the coefficients, and X1…n are the independent (predictor) variables. In logistic regression, the dependent variable is coded to distinguish the difference between occurrence and nonoccurrence of an event. Assigning a value of 1 (Y=1) to event occurrence and 0 (Y=0) to non-occurrence of the event is the simplest coding for the dependent variable. The parameters of the model were estimated using the SPSS software. The sign and significance of the estimated coefficients indicate the direction and strength of influence of each factor on the probability of establishment of ATCs. To facilitate interpretation, the estimated coefficients were converted into odds ratios using the exponential function. An odds ratio greater than unity implies that the corresponding variable increases the likelihood of establishing an ATC, while a value less than unity indicates a negative influence. The overall significance and goodness of fit of the model were evaluated using the appropriate test. Variables with statistically significant coefficients were considered as the major determinants responsible for the establishment of Agro-Tourism Centres in the study region.

Result

The result of logistic regression model is presented below.

Omnibus tests of model coefficients

Table 1. Represent the Omnibus test which was used to assess the overall significance of LP model. It tests whether the inclusion of the independent variable significantly improves the model's ability to predict the dependent variable compare to a model containing only the intercept. It was observed from the Table 1 that the omnibus test yielded a chi-square value of 179.08, which was statistically significant indicated that, the logistical regression model provides a substantially better and set of independent variables collectively contributed to explain the establishment of ATC.

Model summary

The Model summary was depicted in

Hosmer and lemeshow Test

Hosmer and Lemeshow statistic was used to assessed the goodness of fit of the logistic regression model by comparing the observed and predicated probabilities of the dependent variable. The non-significance results predicted that the there was no significant difference between the observed and predicted values, indicated that the logistic regression model was fitted the data satisfactorily. The distance from the main road exhibited a negative and significant relationship with the establishment of Agro tourism centres (B = -0.772; p < 0.01). The odds ratio [Exp(B) = 0.462] implies that an increase in the distance from the main road reduces the likelihood of establishing an Agro tourism centre by approximately 53.8 per cent. This indicates that easy accessibility is an important determinant for attracting tourists and promoting Agro tourism. The variable distance from the nearby tourist spot had a positive and statistically significant influence on the establishment of Agro tourism centres (B = 0.123; p < 0.01).

The estimated odds ratio [Exp(B) = 1.131] indicates that with every one-kilometre increase in distance from a nearby tourist spot, the odds of establishing an Agro tourism centre increase by 13.1 per cent. this revealed that the Agro tourism centres were often established at locations slightly away from major tourist attractions, where agricultural land is more readily available and the natural rural environment could be preserved. Moreover, many tourists visiting Agro tourism centres prefer peaceful, scenic, and less crowded destinations that provide relaxation and an authentic farm experience rather than congested tourist locations. The estimated coefficient for farming experience was negative and statistically significant at the 10 per cent level (B = -0.088; p = 0.064

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