Identification of the Potential to Introduce Mobile Based-Demand and Supply Forecasting System for Potato Farmers: A Case in Nuwara Eliya District
T.B. Mallikaarachchi1*, G.C. Samaraweera1, W.A. Indika2 and M.K.S. Madushika2
1Department of Agricultural Economics, Faculty of Agriculture, University of Ruhuna, Sri Lanka
2Department of Computer Science, Faculty of Science, University of Ruhuna,
Sri Lanka
*tbmallikaarachchi@gmail.com
In Sri Lanka, potato farmers commonly face uncertainties regarding supply and demand. Therefore, most of the farmers used to take their decisions based on the rough measurements, or informal/formal recommendations. This leads to occur over-supply resulting food wastage and price dropdown. To overcome this situation, this study was conducted to identify the potential on providing future demand and supply information through mobile-based information system in planning stage. This research study was conducted in Nuwara Eliya district by selecting 50 potato farmers using Snowballed sampling method. Then, selected farmers’ willingness was captured by using pretested questionnaire. Collected data were analyzed by using one-way ANOVA. According to the results of one- way ANOVA, age of the farmers (p= 0.05), gender (p = 0.05) and education level (p= 0.000) showed the strong significant relationship with willingness to have mobile-based demand and supply forecasting system while farmers’ employment status (p = 0.080) and their farming type (p = 0.068) showed the marginal significant relationship. Moreover, when comparing the mean values within the categories, 20-30 age group (Mean = 4.80) in age category, male farmers (Mean = 4.36) in gender category, farmers educated up to GCE A/L (Mean = 4.75) in education category, farmers who engaging other sectors as their fulltime occupation and doing part time potato farming (Mean = 4.67) in employment status category, and farmers doing contract farming (Mean = 5.00) in farming type category showed the highest mean values within the category that they belonged. Therefore, these farmers tend to have mobile-based demand and supply forecasting system for their decision-making process than the other farmers . Accordingly, there is a high potential to introduce mobile-based demand and supply forecasting system for male, educated farmers up to GCE A/L who belong to 20-30 age group, who do part time potato farming, and who engaged in contract farming at the initial stage. These findings provide promising avenues for future research related to other crops as well in this regard.
Keywords: Demand and supply, Forecasting, Mobile-based information system, Potato Farming
Analysis of Resource Use Efficiency in Chilli Production and Its Contribution to Household Farm Income in Manmunai South and Eruvilpattu DS Divisions, Batticaloa
S. Tharmitha* and K. Sooriyakumar
Department of Agricultural Economics, Faculty of Agriculture, University of Jaffna, Sri Lanka * tharmithasathathevan@gmail.com
Chilli is one of the major cash crops grown in Sri Lanka. The resource use efficiency in chilli production has a significant contribution to household income. Technical efficiency is determined by several efficiencies and inefficiency variables. The major objective of this study was to analyse the resource use efficiency and its contribution to household farm income in Manmunai South and Eruvilpattu DS divisions. Quantity of urea, NPK, organic fertilizer and pesticides and method of irrigation were included as explanatory variables in the production function. Age of farmer, education, involvement, experience, extension services and the number of plants in the field were considered as the factors for the inefficiency of chilli production. Descriptive statistics, and Cobb Douglas stochastic frontier production function were used to analyse data. The result of this study shows that, in Cobb Douglas production function, the coefficient of urea (0.1) is positive and significant. It indicates that if the quantities of urea per plant increase by 1%, it increases the yield of green chilli per plant by 0.1% while other things equal. In the inefficiency model, the number of plants in the farm was positive and significant. The coefficient of number of plants indicates that number of plants in the farm increases by 1000 units, the inefficiency of the farm increases by 2%. The average technical efficiency of chilli production in this study area is around 81%. Variations in the efficiency of chilli productivity in the farms were around 81%. Therefore, there is high potential to increase the efficiency in chilli production by 19% with available current technology. This study indicates that small chilli farms are more efficient than large chilli farms. Therefore, Department of Agriculture should provide materials and technical assistances to small farms to increase the efficiency and chilli total production in this study area.
Keywords: Chilli, Inefficiency, Productivity, Resource use efficiency