This study was conducted to identify and analyse factors affecting marketing of vegetables among small-scale farmers in West Bengal. Data collected with structured questionnaire and analyzed using descriptive and regression analysis. Data collected from 80 vegetable growers selected from Cooch Behar using structured interview schedule and analyzed through econometric techniques. Regression analysis showed that the factors like price, production, farm size, extension contact, competition, transportation, etc. determine the arrival of vegetable crops in the market. Correlation analysis among the variables from demand-side showed that population growth, per capita income and production level had positive correlations with market arrival (demand) of vegetable crops. The study recommended higher investment, favourable government policy, quality of produce, post-harvest facilities, etc. for improving overall marketing efficiency.

Population growth, per capita income, and production level of vegetables had positive relationship with market arrival (demand side) of vegetable crops.

Price had remained to be the most important independent variable to determine the volume of market arrival when analyzed from both supply-side and demand-side.

The study is based on the primary data collected randomly and purposively from different market functionaries during 2019-20 with help of structured schedule. Technique of simple random survey was purposively. The respondents were approached personally when market was in operations for interview and secondary information was also collected from the journals, magazine, periodicals, government sources, websites, etc.. The crops were selected namely Potato, Tomato, Chilli and Brinjal. The selection was done based on Surplus Production of Coochbehar district of West Bengal was selected purposively. Out of 12 blocks of Coochbehar district, two blocks namely, Coochbehar-I and Coochbehar– II, had been selected purposively. From these two blocks, 8 markets were selected randomly. Lastly, 4 markets from each blocks namely, Ghunghumari hat, Daowaguri hat, Dewanhat, Satmail hat in Coochbehar-I and Pundibari, Rajarhat, Dodearhat and Baneswar in Coochbehar-II were fixed up purposively in West Bengal. Thus, the study was done with total respondents of 80 for obtaining field data.

Econometric tool like multiple regression analysis was use to find out independent variables/factors responsible for determining the level/quantity of arrival/supply of vegetable crops in the market. The factors selected in this analysis were from supply side. The mathematical expression of the multiple regressions is given below:

Where,

_{1} = Age (Years)

_{2} = Farm size (ha)

_{3} = Extension contact (Dummy variable)

_{4} = Price (₹)

_{5} = Length of marketing channel (Nos.)

_{6} = Expected price (Dummy variable)

_{7} = Production (Dummy variable)

_{8} = Distance to market (Km)

_{9} = Demand in the market (Dummy variable)

_{10} = Transportation (Dummy variable)

_{11} = Competition between farmers (Dummy variable)

_{12} = Storage facilities

_{i}

Correlation is a statistical method that measures whether or not the pairs of variables are linearly related. Results of correlation coefficient between dependent (market arrival) and independent variables would show the positive or negative linear effect/relationship. A correlation statistic, which is used to know the degree and direction of association between two variables, is known as Pearson correlation coefficient. The correlation coefficient is denoted by

Where,

This section encompasses the issues related to the factors which were assumed to be the probable factors to influence the level of arrival of selected vegetable crops in the different retail markets. The econometric model like technique of multiple regression analysis had been adopted for this purpose. Values of the selected supply side independent variables as obtained through field survey have been used. The model had been applied to all the selected crops separately. The estimates have also been shown crop-wise.

The values of the estimates of different independent variables which were incorporated in the multiple regression models have been shown in the _{2} = 0.872), price of the potato (_{4} = 3.154), length of marketing channel (_{5} = 0.028), farm production level (_{7} = 0.146), market demand (_{9} = 5.426) and transport facilities (_{10} = 1.025) have positive and significant effect on market arrival of potato. Age, extension contact, expected price, etc. were positive but not significant. An estimate of distance between farm and market implies negative impact on market arrival. R^{2} (Multiple regression co-efficient) values (0.72) is also significant at 1% probability level.

Estimates of Multiples Regression Analysis for Potato

The values of the estimates of different independent variables which are incorporated in the multiple regression models have been shown in the _{2} = 0.09), price of the tomato (_{4} = 1.50), length of marketing channel (_{5} = 0.20), farm production level (_{7} = 0.55), transport facilities (_{10} = 2.648) and competition between producers (_{11} = 0.034) have positive and significant effect on market arrival of tomato. Among them, estimates of market price and competition between the producer-farmers have more impact as they are significant at 1% probability level. Age, extension contact, market demand, etc. have insignificant impact on market arrival. Distance has a negative effect. R2 value (0.78) remains to be significant at 1% probability level.

Estimates of Multiples Regression Analysis for Tomato

The values of the estimates of different independent variables affecting the arrival level in the market which are incorporated in the multiple regression model have been shown in the _{2} = 1.24), price of the chilli (_{4} = 1.43), length of marketing channel (_{5} = 0.08), farm production level (_{7} = 0.05) and market demand (_{9} = 1.606) have positive and significant effect on market arrival of chili. Among them, estimates of market price and market demand have more impact as they are significant at 1% probability level. However, transport, expected price, competition, etc. have positive impact but are not significant. Age and distance remain to be the factors with negative impact on market arrival. R^{2} value (0.82) is also found to be significant at 1% probability level.

Estimates of Multiples Regression Analysis for Chilli

The values of the estimates of different independent variables affecting market arrival which are incorporated in the multiple regression models have been shown in the

Estimates of Multiples Regression Analysis for Brinjal

The values of the estimates show that extension contact (_{3} = 0.002), price of the brinjal (_{4} = 1.10), length of marketing channel (_{5} = 0.17), farm production level (_{7} = 0.10), transport (_{10} = 0.567), market demand (_{9} = 1.154) and competition between the farmer-producers (_{11} = 1.345) have positive and significant effect on market arrival of brinjal. Among them, estimates of market price, length of market channel, market demand and competition have more impact as they are significant at 1% probability level. However, farm size and expected price have positive impact but are not significant. Distance as usual has a negative effect on market arrival. R^{2} value (0.76) is found to be significant at 1% probability level.

The study of multiple regression analysis, thus, shows that market arrival of vegetable crops depends upon some common factors like farm size, production level, price, transportation, length of marketing channel, market demand, etc. They have positive influence. However, other selected variables like extension contact, expected price, competition, etc. have also impact on supply of vegetables in the market, but, their strengths of effect are not significant.

Estimates of correlation coefficient (

In view to ascertain the strength of the factors/ variables which influence the extent of arrival of vegetables in the market for purchase by the consumers, statistical tools of correlation coefficient had been attempted. Details of the estimates are presented in the

The values of correlation coefficient show that population growth (

Vegetable marketing is crucial to achieve the overall goals of sustainable agriculture, food security, and poverty reduction, especially among small-scale farmers in rural areas. Econometric model (multiple regression analysis) was fitted and estimated to find out the important independent variables, which were supposed to influence the volume of market arrival from supply-end. The significant factors determining the arrival of vegetable crops positively in the market were price, production, farm size, extension contact, competition, transportation etc. The factors like distance to market and length of marketing channel are found to affect negatively. Correlation analysis on the variables from demand-side showed that population growth, per capita income and production level had positive correlations with market arrival (demand) of vegetable crops. Estimate of correlation coefficient between demand for vegetables and percentage share on consumption of vegetables show linear and positive association. Though the estimate was not significant. On the other hand, retail price had negative impact on market (consumer) demand as depicted with negative value of correlation coefficient. Vegetable markets were of similar pattern in operation. Price had remained to be the most important independent variable to determine the volume of market arrival when analyzed from both supply-side and demand-side. Few suggestions in terms of higher investment, govt. policy, quality produce, post- harvest facilities, etc. were made for overall marketing efficiency.