Factors influencing smallholder cocoa production : a management analysis of behavioural decision-making processes of technology adoption and application
The objectives of the study were to expand present knowledge on the technology adoption and application rates for production inputs and fermentation processing related to farmers' decision- making, and to formulate an optimal technology application policy, particularly for smallholder cocoa farmers. To achieve these objectives it is necessary to understand factors that are associated with farmers' decision-making in adopting and applying these technologies and problems related to them. Given the two objectives, the study develops and tests (1) a model that assesses factors which explain cocoa farmers' technology adoption and application, and (2) a model that presents the optimization of cocoa fanners' activities both at the cocoa farmer and regional level.This research was carried out in South-Sulawesi, Indonesia. This choice was motivated by the fact that (1) on the whole, cocoa in this region is grown by smallholder farms; South-Sulawesi is the region which makes most significant contribution to national cocoa production; (2) this region is the main cocoa producer in the area providing about 32 percent of the national cocoa production; and (3) this region was one of the earliest cocoa regions to be developed. At the sub-region level two villages, Noling and Buntu Batu , with similar enviromnental conditions, in the regency of Luwu , were chosen to represent the villages that had adopted cocoa technology to a greater and respectively to a lesser degree. The two villages were the first to develop cocoa in the region and housed multiethnic inhabitants who were the pioneers of cocoa development in the region.This study has been carried out on the basis of inductive methodology. This case study explores the diversity and the heterogeneity of farmers' behaviour under specific socioeconomical conditions. The number of farmers chosen as respondents in the study in the two villages was 100, 50 for each village. The model was developed on the basis of two approaches, namely a positive approach in which empirical analysis uses production function methods, and a normative approach in which linear programming models are used as a tool of analysis.The models concentrate on the specific issue of cocoa smallholder farmers and their problems in adopting and applying certain available technology which focuses the investigation on certain elements in the model. The issues considered are all aspects related to farm and farmer characteristics, conditions and problems that constrain the cocoa farmers in achieving their objectives. The first element of the model developed is the objectives' function which is specified in terms of technology adoption and application by cocoa farmers. The second element of the model is data that relate to factors that may explain the variation in the use of technologies. The third element of the model is the set of independent variables that are treated as given variables within the cocoa farmer's operations. It is assumed that farmers' behavioural decision-making is determined by the farmers' strategies as controllable factors. The farmers' strategies embody the farmer and farming factors. The technology adoption model of study includes six specific factors, which are grouped into four main groups: farmer community, farmer's characteristics, farmer's household and farm characteristics as independent variables. The technology application model includes all production inputs used, land, labour and chemical production inputs as independent variables. The latest element ofthe model is the dependent variable. Four technology adoption variables, which are fertilizer, pesticide, herbicide and fermentation adoption are included as dependent variables in the model of technology adoption of the study, and farm gross output is included as dependent variable in the model of technology application.The results of the analyses showed that the main factors explaining technology adoption and application are the origin of farmers, the number of neighbours known intimately, the number of family workforce members, years in education, annual crop area exploited and farm gross output. These factors affect different technology adoption and application at different levels:Origin of farmer. This affects fertilizer and herbicide application negatively and has insignificant correlation with technology application. The migrant farmers who mostly housed in the first village are significantly lesser adopted fertilizer and herbicide. This occurs since most of cocoa area exploited by farmers from the first village is located at a more distant site from the village, on the upland areas, which are although usually less fertile than the plots located close to the village; however, the lack of infrastructure in this region contributes to the limited adoption on fertilizer. The indigenous farmers who mostly have a larger area than the migrant farmers have adopted herbicide more than the migrant farmers, in their effort to minimize the use of labour for weed control.The number of neighbours known intimately. This affects fertilizer adoption negatively and fermentation adoption positively. Fertilizer is more adopted by the farmer families with smaller number of acquaintances, which are usually those who came later in the region and have smaller farms. This is different with fermentation adoption. Fermentation has been more adopted by farmers with more neighbours than by farmers with smaller social networks. The farmers who usually have wider relationship with other farmers have better access to the source of information about market development, including the cocoa price development over time. Farmers with information about the market have a better chance to obtain a higher price for their fermented cocoa. The price factor is the main determinant in the farmer decision to ferment their cocoa. The number of neighbour family knowing intimately has also a significant correlation with technical efficiency of cocoa production. Farmers with better access to the source of technical information have more knowledge of technology application.Years in education. This influences pesticide adoption and technical efficiency positively. Literate farmers are more likely to adopt pesticide than illiterate farmers. Farmers with higher education levels are generally the younger fanners who started their cocoa farming business recently, who usually exploit distant plots, that usually have lower levels of soil fertility and have a smaller farming area. To increase production they have to adopt pesticide.Number of family workforce members. This influences fertilizer and pesticide adoption negatively and has a significant correlation with technology application. Farmers with a lower number of family workers have adopted more fertilizer and pesticide than those with a larger number of family workers. The former are the farmers who exploit a smaller number of cocoa hectares and/or younger farmers who usually attempt to exploit their plot intensively by using fertilizer and pesticide in order to increase cocoa production on their limited farm area. The result also imply a negative relationship between the number of family and technology adoptions in the case of fertilizer and pesticide adoption, and a positive relationship between years in education and pesticide application; however, no relationship could be found between the age of farmers and technology adoption, and relationships between the distance of plots from the village and technology adoptions. Once technology is adopted, the level of technology application which is represented by technical efficiency has significant correlation with the number of family workforce members.Annual crop area exploited. This factor does not affect technology adoption. Annual crop area exploited influences technology application positively; farmers who successfully expand their farms with wet paddy areas use more production inputs and apply more fermentation than the farmers without paddy crop plots. This is understandable since in general wet paddy area in the region has been exploited intensively by regularly applying production inputs in high doses, an unavoidable practice if the food requirements of the farmer's family are to be met. The farmers who also exploit the annual crop area have more ability in operating their farm than the farmers without paddy plots. The farmers who have fulfilled their basic family food requirements from their own farm have a better opportunity for spending their budget for purchasing production inputs.Farm gross output. Farm gross output has a positive relationship with pesticide adoption and technology application. The larger farmers tend to adopt more pesticide than the smaller farmers. Farm gross output in a previous year has also a positive and significant correlation with the technical efficiency of cocoa production. The higher the gross output of the previous year, the higher the ability to purchase production inputs and apply fermentation.The second, normative model used in the study is a linear programming model that focuses on the farm level activities based on different kinds of technologies. The farm condition is assumed to be stable, risk and time dimensions are not included in the model. Three main situations of farm activities are differentiated based on the contribution of the source of farmer income. Cocoa is cultivated as a single crop, cocoa and other perennial crops are cultivated as mixcrops on the same plots, cocoa plots are combined with annual plots, and cocoa and other crops are supplemented by off-farm activities. The main objective of farm households is to achieve an optimal farm gross margin that can be realized through the optimization of the gross margin of several crops described and off- farm activities. The technology used is divided into pre-harvest and post-harvest technology. Three levels of preharvest technology are used as the basis of analysis, extensive with no application of external inputs, intensive with a high level of inputs and semi-intensive with an intermediate level of inputs. Two levels of post-harvest technology are used, non-application and application of fermentation, which imply the direct and indirect sale of unfermented and fermented cocoa. A part of the family workforce works as a salaried workforce at other farms during the cocoa harvest and at other peak season periods; i.e. off-farm activity. Farms are subject to various constraints: the farm size exploited, the suitability of land used for different crops, the available family workforce and the seasonal peak requirement of labour for each activity.The result of the optimization analysis shows that the best optimal farm solution is achieved in the farm situation with the most diversified activities. This is the case in the farm situation with mixed cropping of cocoa, wet paddy plots and off-farm activities. In this situation the farm gross margin obtained for each level of farm size is always higher than other types of farm systems. This achievement is possible since the optimal farm plan is generated by (1) making optimal use of the land available by application of crops' technology, both by a best single technology and the most appropriate combination of various technologies, (2) an optimal implementation of cocoa-processing technology through fermentation application, (3) an optimal employment of family workforce for both on-farm and off-farm activities. The best optimal gross margin obtained for a sole cocoa plantation is achieved on a farm size of 3 hectares with intensive cocoa treatment. For cocoa intercropping, the best result is obtained by intensive cocoa combined with hiring labour from outside farms.The conclusions of the study are that in the last two decades the development of the farming system in the region, dominated by cocoa, has changed profoundly. This is due to the land suitability and the dynamic behaviour of indigenous and migrant farmers in adopting and making use of the technology and resources available. Farmers' decisions in adopting cocoa technology are determined by the origin of farmers, the number of neighbours known intimately, the level of education, the number of family workforce and farm gross output factors, while for application technology they were determined by the number of neighbours known intimately, education level, the number of family labour, annual crop area exploited and farm gross output factors. Fertilizer adoption is explained by the origin of farmers, the number of neighbours known intimately and the number of family labour. Pesticide adoption is explained by education level, the number of family labour and farm gross output factors. Herbicide adoption is affected by the factor's origin of farmer. Fermentation adoption is affected by the number of family labour. Technology application is affected by the number of neighbours known intimately, education, the number of family labour, annual crop area exploited and farm gross output factors. The optimization analysis confirms that there is a room to optimize the existing cocoa farmers' practice of the region. Under various constraints of land, labour and crop production treatment, the optimal level of the farm margin may possibly be achieved by making optimal use of the land, introducing a more appropriate application of technology and employing family labour optimally, in both on-farm and off-farm activities.Factors that are associated with farmers' decision making in adopting technology, have clarified our insight into farmers' appreciation of cocoa technology adoption. Farmers adopting technology when cultivating cocoa as a perennial crop are looking towards the long term objective and the long term investment, which is the average projected returns over a number of years will be the most significant farmer objective. However, many other aspects still contribute to cocoa development. Firstly , a comprehensive study of appropriate farming system models under the conditions of the region including the ecological evidence for promoting cocoa and perennial crops as a sustainable alternative. Secondly , the positive implications of technological adoption and application both at farmers and regional level need to be clarified to determine the optimal benefits. Thirdly , a study of integrated cocoa development that taking into account all agribusiness aspects is advisable. This study could identify the strong and weak points of the cocoa smallholder's bargaining position.
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| Format: | Doctoral thesis biblioteca |
| Language: | English |
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Landbouwuniversiteit Wageningen
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| Subjects: | cocoa, decision making, farm management, innovations, linear programming, management, operations research, simulation, small farms, sulawesi, theobroma cacao, work flow, agrarische bedrijfsvoering, bedrijfsvoering, besluitvorming, cacao, celebes, innovaties, kleine landbouwbedrijven, lineair programmeren, operationeel onderzoek, simulatie, werkschema, |
| Online Access: | https://research.wur.nl/en/publications/factors-influencing-smallholder-cocoa-production-a-management-ana |
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