This paper estimates the determinants of farmers’ self-perception toward adoption of new agricultural technologies based on a primary survey of 731 farm households that cultivated rice in eastern Indian states: 157 of these households received seed mini-kits of a new stress-tolerant rice variety called Swarna-Sub1, and the remaining 574 households were randomly selected from the study regions. The results show that farmers who received Swarna-Sub1 have higher scores on self-perception indices toward adoption of new agricultural technologies than the representative farmers. The paper also identifies factors that influence self-perception. The results indicate that female farmers, the less educated farmers, and farmers who belong to the scheduled caste group have low scores on self-perception indices, whereas Swarna-Sub1 users, large landholders, and wealthy farmers have high scores. The results suggest that empowering farmers, in terms of self-perception, may lead to adoption of new technologies.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Price includes VAT (USA)
Tax calculation will be finalised during checkout.
Feder and Savastano (2006) analyzed how opinion leaders’ views on a technology affect adoption of the technology of others.
In Uttar Pradesh state, the surveyed districts include Gorakhpur, Maharajganj, Sidhartnagar, Sant Kabir Nagar, Basti, and Mau while Puri and Khurda in Odisha state were covered.
Nand Educational Foundation for Rural Development (NEFORD) in Uttar Pradesh and Association for India’s Development (AID) in Odisha.
Kharif is the main agricultural season in Eastern India.
In general, using Scree Test Criterion enables one to use more factors than using any other criterion.
Similarly, Singh et al. (2012a) also found similar results in the context of micro-insurance in Gujarat State of India. In addition, Munasib and Roy (2012) found that caste affiliation plays an important role in adoption of new technologies. The author concluded that there is a strong and positive association between group adoption and choice of a modern variety by an individual farmer who grow Pearl Millet in Rajasthan in India.
Ajzen I (1991) The theory of planned behavior. Organ Behav Hum Decis Process 50:179–211
Ajzen I, Fishbein M (1980) Understanding attitudes and predicting social behavior. Prentice-Hall, Englewood Cliffs
Azman A, Silva JLD, Samah BA, Man N, Shaffril HAM (2013) Relationship between attitude, knowledge, and support towards the acceptance of sustainable agriculture among contract farmers in Malaysia. Asian Soc Sci 9(2):99–105
Beedell J, Rehman T (2000) Using social-psychology models to understand farmers’ conservation behavior. J Rural Stud 16:117–127
Burton RJF (2004) Reconceptualising the ‘behavioural approach’ in agricultural studies: a socio-psychological perspective. J Rural Stud 20(2):359–371
Cramerer CF, Loewenstein G (2004) Behavioral economics: past, present, and future. In: Cramerer CF, Loewenstein G, Rabin M (eds) Advances in Behavioral Economics. Princeton University Press, New York, pp 3–51
Dar MH, de Janvry A, Emerick K, Raitzer D, Sadoulet E (2013) Flood-tolerant rice reduces yield variability and raises expected yield, differentially benefitting socially disadvantaged groups. Sci Rep. doi:10.1038/srep03315
Datta S, Mullainathan S (2013). Behavioral design: a new approach to development policy. Center for Global Center. CDG Policy Paper. 16 (November)
Deshpande A (2001) Caste at birth? Redefining disparity in India. Rev Dev Econ 5(1):130–144
DeVellis RF (2003) Scale development: theory and applications, 3rd edn. Applied Social Research Methods Series, Vol. 26. Sage Publications, Inc.
Doss CR (2008) Analyzing technology adoption using microstudies: limitations, challenges, and opportunities for improvement. Agric Econ 34(3):207–219
Doss CR, Morris M (2000) How does gender affect the adoption of agricultural innovations? The case of improved maize technology in Ghana. Agric Econ 25(1):27–39
Fan CC, Yu XQ, Xing YZ, Xu CG, Luo LJ, Zhang Q (2005) The main effects, epistatic effects and environmental interactions of QTLs on cooking and eating quality of rice in a doubled haploid line population. Theoret Appl Genet 110:1445–14452
Feder G, Savastano S (2006) The role of opinion leaders in the diffusion of new knowledge: the case of integrated pest management. World Dev 34(7):1287–1300
Feder G, Just RE, Zilberman D (1985) Adoption of agricultural innovations in developing countries: a survey. Econ Dev Cult Chang 33(2):255–298
Foster A, Rosenzweig M (1995) Learning by doing and learning from others: human capital and technical change in agriculture. J Polit Econ 1003(6):1176–1209
Foster A, Rosenzweig M (2010) Microeconomics of technology adoption. Annu Rev Econ 2:395–424
Garforth C, Rehman T, McKemey K, Tranter R, Cooke R, Yates C, Park J, Dorward P (2004) Improving the design of knowledge transfer strategies by understanding farmer attitudes and behavior. J Farm Manag 12(1):17–32
Hair J, Black W, Babin B, Anderson R (2010) Multivariate data analysis, 7th edn. Prentice Hall, Upper Saddle River
Hansson H, Ferguson R, Olofsson C (2012) Psychological constructs underlying farmers’ decisions to diversify or specialize their business—an application of theory of planned behavior. J Agric Econ 63(2):465–482
Ismail AM, Singh US, Singh S, Dar MH, Mackill DJ (2013) The contribution of submergence-tolerant (sub1) rice varieties to food security in flood-prone rainfed lowland areas in Asia. Field Crop Res 152:83–93
Lapar MLA, Ehuri SK (2004) Factors affecting adoption of dual-purpose forages in the Philippine uplands. Agric Syst 81(2):95–114
Lapple D, Kelley H (2013) Understanding the uptake of organic farming: accounting for heterogeneities among Irish farmers. Ecol Econ 88:11–19
Martínez-García CG, Dorward P, Rehman T (2013) Factors influencing adoption of improved grassland management by small-scale dairy farmers in central Mexico and the implications for future research on smallholder adoption in developing countries. Livestock Sci 152:228–238
Moser CM, Barrett CB (2006) The complex dynamics of smallholder technology adoption: the case of SRI in Madagascar. Agric Econ 35(3):373–388
Munshi K (2004) Social learning in a heterogeneous population: technology diffusion in the Indian green revolution. J Dev Econ 73:185–213
Ragasa C (2014) Improving gender responsiveness of agricultural extension. In Quisumbing AR, Meinzen-Dick RS, Raney TL, Croppenstedt A, Behrman JA, Peterman A (eds) Gender in agriculture: closing the knowledge gap, Chapter 17. Springer, Netherlands, pp 411–430
Rehman T, Mckemey K, Yates CM, Cooke RJ, Garforth CJ, Tranter RB, Park JR, Dorward PT (2007) Identifying and understanding factors influencing the uptake of new technologies on dairy farms in SW England using the theory of reasoned action. Agric Syst 94(2):281–293
Rogers EM (2003) Diffusion of Innovations, 5th edn. Free Press, New York
Serraj R, McNally KL, Slamet-Loedin I, Kohli A, Haefele SM, Atlin G, Kumar A (2011) Drought resistance improvement in rice: an integrated genetic and resource management strategy. Plant Prod Sci 14(1):1–14
Shah G, Mander H, Thorat S, Deshpande S, Baviskar A (2006) Untouchability in Rural India. Sage, New Delhi
Singh A, Gaurav S, Ranganathan T (2012a) Do caste and social interactions affect risk attitudes and adoption of microinsurance? Evidence from rainfall insurance adoption in Gujarat, India. Research Paper no. 25. International Labour Office, Geneva
Singh KM, Jha AK, Meena MS, Singh RKP (2012b) Constraints of rainfed rice production in India: an overview. In Shetty PK, Hedge MR, Mahadevappa M (eds) Innovations in rice production. National Institute of Advance Studies, Indian Institute of Science, Bangalore, pp 71–84
Willock J, Deary IJ, McGregor MM, Sutherland A, Edwards-Jonesa G, Morgana O, Dentc B, Grieved R, Gibsone G, Austine E (1999) Farmers’ attitudes, objectives, behaviors, and personality traits: the Edinburgh study of decision making on farms. J Vocat Behav 54(1):5–36
The authors wish to express their appreciation to Dr. Anne Marike Lokhorst from Wageningen University for her valuable comments and suggestions on the final draft of this paper. The authors wish to acknowledge the financial support from the Stress Tolerant Rice for Africa and South Asia (STRASA) Project, supported by the Bill and Melinda Gates Foundation (BMGF). We thank the district authorities in the study area and all enumerators who were involved in data collection, analysis and report compilation.
Conflict of interest
The authors have not declared any conflict of interest.
About this article
Cite this article
Yamano, T., Rajendran, S. & Malabayabas, M.L. Farmers’ self-perception toward agricultural technology adoption: evidence on adoption of submergence-tolerant rice in Eastern India. J. Soc. Econ. Dev. 17, 260–274 (2015). https://doi.org/10.1007/s40847-015-0008-1
- Psychological constructs
- Behavioral economics
- Stress-tolerant crop
- Social groups
- Schedule caste