An innovation system perspective of two dairy value chains in Kerala
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Keywords:
Convergence, Ego networks, Kerala, Linkages, Social network analysisAbstract
Although recognized that collaborative performance of the diverse actors are crucial for the success of a value chain, there have been few efforts to understand their dynamics of linkages and interactions in context of dairying. This study fills the gap by analysing the convergence among various actors of 2 dairy value chains (SBCMSS and PDDP) with an innovation system focus. Key informant interviews supplemented with household level suvey among the livestock rearers were conducted to collect data. Snowball sampling was followed to identify diverse actors of value chains followed by simple random sampling for mapping the innovation system. Data were analysed using Social Network Analysis (SNA). Results indicate that dairy farmers hold the key influencive position in the ego network of SBCMSS and the private dairy firm in case of PDDP. However, the network members of SBCMSS were more likely to access various resources and services than that of PDDP. Besides, there is a considerable scope for enhancing the linkages among the actors for better interaction. Higher centrality measures for the farmers in terms of information brokerage and proximity to the other actors were desirable results for the future extension and technology dissemination interventions. Policy makers could focus on fixing the gaps in linkages between the actors and reconfiguring the interactions to strengthen the central actors to improve the performance of innovation system.
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References
Agricultural Development Policy. 2013. Government of Kerala. [Retrieved from http://www.keralaagriculture.gov.in/pdf/dap_e_15072013.pdf] [Accessed on 13 February 2015].
Anonymous. 2017. Discussion draft on approach paper for 13th FYP (Unpublished). Kerala State Planning Board. DOI: https://doi.org/10.5194/bg-2017-113-RC1
Anandajayasekeram P and Gebremedhin B. 2009. Integrating innovation systems perspective and value chain analysis in agricultural research for development: Implications and challenges. Working Paper No.16, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia.
Ayele S, Duncan A, Larbi A and Khanh T T. 2012. Enhancing innovation in livestock value chains through networks: Lessons from fodder innovation case studies in developing countries. Science and Public Policy 39(3): 333–46. DOI: https://doi.org/10.1093/scipol/scs022
Basic Animal Husbandry & Fishery Statistics (BAH&FS). 2015. Government of India, Ministry of Agriculture, Department of Animal Husbandry, Dairying and Fisheries, Krishi Bhawan,New Delhi. [Retrieved from http://dahd.nic.in/dahd/WriteReadData/Final%20BAHS%202014%2011.03.2015.pdf] [Accessed on 1 June 2016].
Bastian M, Heymann S and Jacomy M. 2009. Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media. pp. 361–362. DOI: https://doi.org/10.1609/icwsm.v3i1.13937
Borgatti S, Everett M and Freeman L C. 2002. Ucinet for Windows: Software for Social Network Analysis. Harvard, MA, Analytic Technologies.
Cantner U and Graf H. 2006. The network of innovators in Jena: An application of social network analysis. Research Policy 35(4): 463–80. DOI: https://doi.org/10.1016/j.respol.2006.01.002
CLPR (Centre for Livestock Development and Policy Research). 2014. Trends in Milk Production of Kerala: An Interim Report. Kerala Veterinary and Animal Sciences University, Mannuthy, Thrissur.
Chindime S, Kibwika P and Chagunda M. 2016. Positioning smallholder farmers in the dairy innovation system in Malawi: A perspective of actors and their roles. Outlook on Agriculture 45(3): 145–50. DOI: https://doi.org/10.1177/0030727016663532
Davis K E, Spielman D J, Negash M and Ayele G. 2006. Smallholder innovation in Ethiopia: Concepts, tools, and empirical findings. Innovation Africa Symposium, pp. 21–23.
Hanneman Robert and Mark Riddle. 2005. Introduction to social network methods. University of California, Riverside (Published in digital form at http://faculty.ucr.edu/~hanneman).
Hilary R S, Sseguya H and Kibwika P. 2017. Information quality, sharing and usage in farmer organizations: The case of rice value chains in Bugiri and Luwero Districts, Uganda. Cogent Food and Agriculture 3(1): 135–47. DOI: https://doi.org/10.1080/23311932.2017.1350089
Klerkx L, Aarts N and Leeuwis C. 2010. Adaptive management in agricultural innovation systems: the interactions between innovation networks and their environment. Agricultural Systems 103: 390–400. DOI: https://doi.org/10.1016/j.agsy.2010.03.012
Mariam A T J M, Jason Y, Paul T K, Droppelmann F and John M. 2016. Who Talks to Whom in Malawi’s Agricultural Research Information Network? Journal of Agricultural Education and Extension 22(1): 7–23. DOI: https://doi.org/10.1080/1389224X.2014.971827
Matuschke I. 2008. Evaluating the impact of social networks in rural innovation systems: An overview (Vol. 816).
International Food Policy Research Institute, Washington. [Retrieved from https://core.ac.uk/download/pdf/6337672.pdf] [Accessed on 3 February 2016].
Methu J, Nyangaga J, Waweru A and Akishule D. 2013. Agricultural innovation systems and value chains development: a training manual. ASARECA, Entebbe, Uganda. [Retrieved from https://www.asareca.org/sites/default/files/publications/AIS%20VCD%20Training%20Manual%20for%20Web.pdf] [Accessed on 15 July 2017].
National Livestock Policy. 2013. Department of Animal Husbandry, Dairying & Fisheries, Ministry of Agriculture, Government of India. [Retrieved from http://dadf.gov.in/dahd/WriteReadData/NLP%202013%20Final11.pdf] [Accessed on 20 January 2016].
Orchard S E, Stringer L C and Quinn C H. 2015. Impacts of aquaculture on social networks in the mangrove systems of northern Vietnam. Ocean and Coastal Management 14(9): 1– 10. DOI: https://doi.org/10.1016/j.ocecoaman.2015.05.019
PDDP. 2000. Peoples Dairy Development Project, Kalady: A brief sketch. PDDP Central Society, Kalady.
Spielman D J, Davis K E, Negash M and Gezahegn A. 2007. Organic rural innovation systems and networks: findings from a study of Ethiopian smallholders. Second International Conference, August 20–22, 2007, Accra, Ghana (No. 52096). African Association of Agricultural Economists (AAAE).
Spielman D J, Davis K, Negash M and Ayele G. 2010. Rural innovation systems and networks: findings from a study of Ethiopian smallholders. Agriculture and Human Values 28(2): 195–212. DOI: https://doi.org/10.1007/s10460-010-9273-y
Thuo M, Bell A A, Bravo-Ureta B E, Okello D K, Okoko E N, Kidula N L and Puppala N. 2013. Social network structures among groundnut farmers. Journal of Agricultural Education and Extension 19(4): 339–59. DOI: https://doi.org/10.1080/1389224X.2012.757244
Weyori A E, Amare M, Garming H and Waibel H. 2017. Agricultural innovation systems and farm technology adoption: findings from a study of the Ghanaian plantain sector. Journal of Agricultural Education and Extension 24(1): 65–87. DOI: https://doi.org/10.1080/1389224X.2017.1386115
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