Linkage Network Structures of Farmers: Analysing FPOs of M.P. and Bihar in India

Authors

  • Ashish Singh Division of Agricultural Extension, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India
  • Rashmi Singh Division of Agricultural Extension, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India
  • Manjeet Singh Nain Division of Agricultural Extension, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India
  • J R Mishra Division of Agricultural Extension, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India
  • Pramod Kumar Division of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India
  • D K Sharma Division of Environmental Sciences, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India
  • Ranjit Kumar Paul Statistical Genetics Division, ICAR-Indian Agricultural Research Institute, New Delhi-110012, India

DOI:

https://doi.org/10.48165/IJEE.2023.59303

Keywords:

Agribusiness linkages, Network analysis, Linkage networks, Farmer Producer Organisation (FPO)

Abstract

Effective linkages among farmers play a crucial role in fostering growth within the agriculture sector. This study conducted during 2020-23 utilizes social network analysis to examine the backward and forward agribusiness linkages of farmers in Dairy Farmer Producer Organizations (FPOs) in Madhya Pradesh and Bihar. Through focused group discussions, a comprehensive list of private and government institutions acting as linkage actors for each FPO were compiled. The findings highlight that farmers primarily rely on strong informal ties for accessing agricultural information and services. Furthermore, a disparity is observed between the FPOs in Bihar and Madhya Pradesh, with the former having a smaller number of linkage actors. The FPO in Bihar demonstrates stronger associations with government institutions and officials, while the FPO in Madhya Pradesh exhibits stronger connections with private entities, including the food processing industry, artificial insemination (AI) technicians, and veterinary doctors. The study provides valuable insights into the connectedness of network actors, underscores the importance of multi-actor alliances, and emphasizes the implications of centrality measures in determining network dynamics. 

Downloads

Download data is not yet available.

References

Anríquez, G., & Stamoulis, K. G. (2007). Rural Development and Poverty Reduction: Is Agriculture Still Key?. eJADE: electronic Journal of Agricultural and Development Economics, 4(853- 2016-56113), 5-46.

Bandiera, O., & Rasul, I. (2006). Social networks and technology adoption in northern Mozambique. The Economic Journal, 116(514), 869-902.

Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). Ucinet 6 for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies.

Chan, K., & Liebowitz, J. (2006). The synergy of social network analysis and knowledge mapping: a case study. International Journal of Management and Decision Making, 7(1), 19-35.

Chindime, S., Kibwika, P., & 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), 143-150.

Cross, R., Parker, A., Prusak, L., & Borgatti, S. P. (2001). Knowing what we know: Supporting knowledge creation and sharing in social networks. Organizational Dynamics, 30(2), 100–120.

Daly, A. J. (2010). Social network theory and educational change. 1st ed. Cambridge, MA: Harvard Education Press.

Das, M., Singh, R., Feroze, S. M., & Singh, S. B. (2020). Determinants of marketed surplus of milk: A micro level study in khasi hills region of Meghalaya. Indian Journal of Extension Education, 56(2), 45–50.

Davis, K. E., Ekboir, J., & Spielman, D. J. (2008). Strengthening agricultural education and training in sub-Saharan Africa from an innovation systems perspective: a case study of Mozambique. Journal of Agricultural Education and Extension, 14(1), 35-51.

Farquharson, K. (2005). A different kind of snowball: identifying key policymakers. International Journal of Social Research Methodology, 8(4), 345–353.

Gorai, S. K., Wason, M., Padaria, R. N., Rao, D. U. M., Paul, S., & Paul, R. K. (2022). Factors contributing to the stability of the farmer producer organisations: A study in West Bengal. Indian Journal of Extension Education, 58(2), 91–96.

Granovetter, M. (2005). The impact of social structure on economic outcomes. Journal of Economic Perspectives, 19(1), 33-50. Hampton, K. N. (2011). Comparing bonding and bridging ties for

democratic engagement: Everyday use of communication technologies within social networks for civic and civil behaviors. Information, Communication and Society, 14(4), 510-528.

Harris, J. K., Luke, D. A., Burke, R. C., & Mueller, N. B. (2008). Seeing the forest and the trees: using network analysis to develop an organizational blueprint of state tobacco control systems. Social Science and Medicine, 67(11), 1669-1678.

Helsley, R. W., & Zenou, Y. (2014). Social Networks and Interactions in Cities. Journal of Economic Theory, 150, 426–466. Kanitkar, A. (2016). The logic of farmer enterprises. Occasional Publication 17 IRMA.

Klerkx, L., Hall, A., & Leeuwis, C. (2009). Strengthening agricultural innovation capacity: are innovation brokers the answer? International Journal of Agricultural Resources, Governance and Ecology, 8(5-6), 409-438.

Kolaczyk, E.D. (2009). Statistical analysis of network data: Methods and models. Springer Series in Statistics. Springer. ISBN 9780387881461

Kumar, S., Sankhala, G., Kar, P., & Sharma, P. R. (2021). An appraisal of financial sustainability of dairy-based farmer producer companies in India. Indian Journal of Extension Education, 57(4), 115–119.

Kumari, N., Malik, J. S., Arun, D. P., & Nain, M. S. (2022). Farmer Producer organizations (FPOS) for linking farmer to market. Journal of Extension Systems, 37(1), 1-6.

Landherr, A., Friedl, B., & Heidemann, J. (2010). A critical review of centrality measures in social networks. Wirtschaftsinformatik, 52, 367-382.

Maertens, A., & Barrett, C. B. (2013). Measuring social networks’ effects on agricultural technology adoption. American Journal of Agricultural Economics, 95(2), 353-359.

Mashavave, T., Mapfumo, P., Mtambanengwe, F., Gwandu, T., & Siziba, S. (2013). Interaction patterns determining improved information and knowledge sharing among smallholder farmers. African Journal of Agricultural and Resource Economics, 8(311- 2016-5612), 1-12.

Matous, P., & Todo, Y. (2015). Exploring dynamic mechanisms of learning

Matuschke, I. (2008). Evaluating the impact of social networks in rural innovation systems: An overview. Discussion Paper, No. 816. International Food Policy Research Institute, Washington, DC.

Ministry of Agriculture and Farmers’ Welfare (2017-18), Annual Report 2017-18, Department of Agriculture and Farmers’ Welfare, Ministry of Agriculture and Farmers’ Welfare, Government of India

Ministry of Agriculture and Farmers’ Welfare (2019-20), Annual Report 2019-20, Department of Agriculture and Farmers’ Welfare, Ministry of Agriculture and Farmers’ Welfare, Government of India

Ministry of Agriculture and Farmers’ Welfare (2022), Annual Report 2021-22, Department of Agriculture and Farmers’ Welfare, Ministry of Agriculture and Farmers’ Welfare, Government of India

NABARD (2019). Farmer producers’ organizations (FPOs): Status, issues and suggested policy reforms. National Level Paper, Potential Linked Plans (PLP) 2019-20.

Nain, M. S., Singh, R., Mishra, J. R., & Sharma, J. P. (2015). Utilization and linkage with agricultural information sources: a study of Palwal district of Haryana state. Journal of Community Mobilization and Sustainable Development, 10(2), 152-156.

Nain, M. S., Singh, R., Mishra, J. R., Sharma, J. P., Singh, A. K., Kumar, A., Gills, R., & Suman, R. S. (2019). Maximising farm profitability through entrepreneurship development and farmers’

innovations: feasibility analysis and action interventions. Indian Journal of Agricultural Sciences, 89(6), 1044-1049. Parthiban Sakthi, R., Nain, M. S., Singh, R., Kumar, S., & Chahal, V. P. (2015). Farmers’ producer organisation in reducing transactional costs: a study of Tamil Nadu mango growers’ federation. Indian Journal of Agricultural Science, 85(10), 1303-1307. Reardon, T., Berdegué, J., Barrett, C. B., & Stamoulis, K. (2007). Household income diversification into rural nonfarm activities. Transforming the rural nonfarm economy: opportunities and threats in the developing world, pp 115-140.

Salokhe, S. (2017). Junnar Taluka farmers producers company limited: A case study on farmers mobilization and empowerment, pp 37- 46.

Stork, D., & Richards, W. D. (1992). Nonrespondents in communication network studies: problems and possibilities. Group and Organization Management, 17(2), 193–209.

Thuo, M. W. (2012). Social Network Effects on Groundnut Farming: The case of Kenya and Uganda. University of Connecticut. Thuo, M., Bell, A. A., Bravo-Ureta, B. E., Okello, D. K., Okoko, E. N., Kidula, N. L., & Puppala, N. (2013). Social network structures among groundnut farmers. The Journal of Agricultural Education and Extension, 19(4), 339-359.

Wang, W., Wang, J., Liu, K., & Wu, Y. J. (2020). Overcoming barriers to agriculture green technology diffusion through stakeholders in China: A social network analysis. International Journal of Environmental Research and Public Health, 17(19), 6976.

Downloads

Published

2023-06-15

How to Cite

Singh, A., Singh, R., Nain, M.S., Mishra, J.R., Kumar, P., Sharma, D.K., & Paul, R.K. (Trans.). (2023). Linkage Network Structures of Farmers: Analysing FPOs of M.P. and Bihar in India . Indian Journal of Extension Education, 59(3), 14–20. https://doi.org/10.48165/IJEE.2023.59303