Role of CSO-CBO Partnership in the aggregation of Agricultural Commodities: Issues and Prospects for Commodity Futures Market Yeswanth D and Sai Krishna.

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Role of CSO-CBO Partnership in the aggregation of Agricultural Commodities: Issues and Prospects for Commodity Futures Market Yeswanth D and Sai Krishna N (Fellow Programme Participants, IRMA, Anand, Gujarat)

10 October 2007National Workshop on Commodity Research2 Setting the context…. Agriculture & allied sectors contribute 22 % GDP (GOI, 2007) 63 per cent - top ten commodities traded (Pitalwalla, 2005). However, agriculture commodity trading faces lots of challenges Decreasing average land holdings and Increasing marketable surplus To add, the existing traditional channel – Low realisation of final price (1/3 rd ) of produce Emergence of alternative models

10 October 2007National Workshop on Commodity Research3 ….Setting the context Alternative models Reduce supply chain cost and Increase share and participation of farmers In the changing scenario …. Commodity exchanges (Price discovery) Amendment of APMC Act A ‘Synergistic model’ Alternative models of aggregation + Commodity Exchanges

10 October 2007National Workshop on Commodity Research4 Existing alternative models Efforts to incorporate best practices Reduction in total supply chain costs Capital investment & Operational expenses Information and Knowledge dissemination But yet to provide a complete solution Supply uncertainties (timeliness and quantities) Trust among partners Poor impact / perceived value among farmers

10 October 2007National Workshop on Commodity Research5 In the above scenario…… New alternative model - emerging CSO-CBO Partnership Model Civil Society Organisation (NGO) Community Based Organisation (SHG) Merits of the CSO-CBO Partnership model Cover –small & marginal farmers (86 %) Scattered and low average land holding Produce contribute Lack of literature on CSO-CBO model

10 October 2007National Workshop on Commodity Research6 Methodology Hypothesis Supply chain of CSO-CBO partnership is efficient than traditional model Universe of the study CSO- CBO Partnership models with successful record of operations in aggregating agricultural commodities

10 October 2007National Workshop on Commodity Research7 …. Methodology Research Design Multiple case study design Sampling Procedure (criteria to be used) Type of Agriculture commodities handled Scale of operations Geographical spread of operations

10 October 2007National Workshop on Commodity Research8 …. Methodology Units of Analysis A case of CSO – CBO Partnership model Dimensions that would be considered Cost Components Organizational Characteristics Partner Relationships Performance Material flow

10 October 2007National Workshop on Commodity Research9 …. Methodology Respondents Farmers Commission agents CSO representatives Traders Data Collection Semi-structured interview schedule Data Analysis Multivariate Analysis

10 October 2007National Workshop on Commodity Research10 Implications of the study Help realise the existing huge potential Potential for sustainability Understanding the modalities of partnership for Synergistic growth

10 October 2007National Workshop on Commodity Research11

10 October 2007National Workshop on Commodity Research12 Variables to be studied Cost components Reduction in total supply chain costs (Pagel, 1999) Economies of scale Capital investment & Operational expenses of model Organizational (CSO & CBO) Characteristics Feasibility of supplier partnering (scaling up feasibility) (Pagel, 1999) Technology quotient of the CSO & CBO Flexibility to the changing market environment (Jha, 2001)

10 October 2007National Workshop on Commodity Research13 …. Variables Partner Relationships Increased perceived value of the bundle of goods and services (Pagel, 1999) Trust among partners (Singh & Bhagat, 2004) Performance Performance of decision support system (Pagel, 1999) Information and Knowledge dissemination (Reach and Richness) (Singh & Bhagat, 2004)

10 October 2007National Workshop on Commodity Research14 …. Variables Material flow Supply uncertainties (Singh & Bhagat, 2004) Timeliness and quantities Reduced time of material flow (Jha, 2001) Reduction in delays in distribution (Jha, 2001)