Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-20T06:52:23.180Z Has data issue: false hasContentIssue false
  • English
  • Français

USING A SOCIO-PSYCHOLOGICAL MODEL TO IDENTIFY AND UNDERSTAND FACTORS INFLUENCING THE USE AND ADOPTION OF A SUCCESSFUL INNOVATION BY SMALL-SCALE DAIRY FARMERS OF CENTRAL MEXICO

Published online by Cambridge University Press:  08 November 2016

CARLOS GALDINO MARTÍNEZ-GARCÍA ,
CARLOS MANUEL ARRIAGA-JORDÁN ,
PETER DORWARD ,
TAHIR REHMAN  and
ADOLFO ARMANDO RAYAS-AMOR
CARLOS GALDINO MARTÍNEZ-GARCÍA
Affiliation:
Instituto de Ciencias Agropecuarias y Rurales (ICAR), Universidad Autónoma del Estado de México (UAEM), Instituto Literario # 100, Col. Centro, Toluca 50000, Estado de México, México
CARLOS MANUEL ARRIAGA-JORDÁN
Affiliation:
Instituto de Ciencias Agropecuarias y Rurales (ICAR), Universidad Autónoma del Estado de México (UAEM), Instituto Literario # 100, Col. Centro, Toluca 50000, Estado de México, México
PETER DORWARD
Affiliation:
School of Agriculture, Policy and Development, University of Reading, PO Box 237, Reading RG6 6AR, UK
TAHIR REHMAN
Affiliation:
School of Agriculture, Policy and Development, University of Reading, PO Box 237, Reading RG6 6AR, UK
ADOLFO ARMANDO RAYAS-AMOR*
Affiliation:
División de Ciencias Biológicas y de la Salud, Departamento de Ciencias de la Alimentación, Universidad Autónoma Metropolitana Unidad Lerma, Av. Hidalgo poniente No. 46 Colonia la Estación, Lerma de Villada 52006, Estado de México, México
*
Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

This paper seeks to make an exploratory investigation regarding farmers who have been using an innovation for a relatively long period (established users), compared to farmers who have only recently started (recent users). Therefore, the aims of this research were to identify (i) the extent to which intentions, attitudes and social pressure are similar or different between these two groups and (ii) whether comparison of the groups can improve academic understanding and provide insights into what is influencing the uptake of innovations. The study was conducted with 80 farmers who are already engaged with the use of improved grassland. In order to develop an understanding of the differences in drivers of the adoption of new technology, the sample was divided into established users and recent users of the innovation. To identify differences between groups regarding farmer and farm characteristics, 11 quantitative variables were analysed through a dependent t-test. The theory of reasoned action (TRA) was used as a theoretical framework and the Spearman rank-order correlation was used in data analyses. To identify differences in farmers’ perceptions of the components of the TRA, we used the Mann–Whitney U test. The results showed that established users had stronger intention to use improved grassland in the next 12 months, which would be attributed to activity based on milk production as a main source of family income. Advantages of improved grassland included lower animal feeding expenses; increases in quantity, quality and availability of fodder production and increases in milk production. We concluded that established and recent users’ intention to use improved grassland over the 12 months was influenced in different ways. Established users’ intention to adopt was strongly influenced by normative beliefs, i.e. social pressure from salient referents, where the father, uncle and veterinarian played the most important role, whereas recent users’ intention was mainly influenced by behavioural beliefs (positive and negative beliefs regarding the innovation) and the variables that describe the farm characteristics, i.e. the advantages and disadvantages that farmers perceive of the use of improved grassland on their farms, which were also considered as drivers of adoption.

Type
Research Article
Information
Experimental Agriculture , Volume 54 , Issue 1 , February 2018 , pp. 142 - 159
Check for updates
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Ajzen, I. (2005). Attitudes, Personality and Behaviour, 2nd ed. Milton Keynes, England: Open University Press.Google Scholar
Ajzen, I. and Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Upper Saddle River, NJ: Prentice-Hall.Google Scholar
Armitage, C. J. and Conner, M. (2001). Efficacy of the theory of planned behaviour: A meta-analytic review. British Journal of Social Psychology 40:471–499.Google Scholar
Borges, R. J. A., Lansink, O. A. G. J. M., Marques, R. C. and Lutke, V. (2014). Understanding farmers’ intention to adopt improved natural grassland using the theory of planned behaviour. Livestock Science 169:163–174.Google Scholar
Bruijnis, M., Hogeveen, H., Garforth, C. and Stassen, E. (2013). Dairy farmers’ attitudes and intentions towards improving dairy cow foot health. Livestock Science 155:103–113.Google Scholar
Bryman, A. and Cramer, D. (2011). Quantitative data analysis with IBM SPSS 17, 18 and 19. In A Guide for Social Scientists. London and New York: Routledge, Taylor and Francis Group.Google Scholar
Carr, S. and Tait, J. (1991). Differences in the attitudes of farmers and conservationist and their implications. Journal of Environmental Management 32:281–294.Google Scholar
Daskalopoulou, I. and Pretrou, A. (2002). Utilising a farm typology to identify potential adopters of alternative farming activities in Greek agriculture. Journal of Rural Studies 18:95–103.Google Scholar
de Lauwere, C., van Asseldonk, M., van't Riet, J., de Hoop, J. and ten Pierick, E. (2012). Understanding farmers' decisions with regard to animal welfare: The case of changing to group housing for pregnant sows. Livestock Science 143:151–161.Google Scholar
Espinoza-Ortega, A., Espinosa-Ayala, E., Bastida-López, J., Castañeda-Martínez, T. and Arriaga-Jordán, C. M. (2007). Small-scale dairy farming in the highlands of central Mexico: Technical, economic and social aspects and their impact on poverty. Experimental Agriculture 43:241–256.Google Scholar
Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics, 4th edn. Great Britain: SAGE Publications.Google Scholar
Garforth, C., McKemey, K., Rehman, T., Tranter, R., Cooke, R., Park, J., Dorward, P. and Yates, C. (2006). Farmer’ attitudes towards techniques for improving oestrus detection in dairy herds in South West England. Livestock Science 103:158–168.Google Scholar
Garforth, C., Rehman, T., McKemey, K., Tranter, R., Cooke, R., Yates, C., Park, J. and Dorward, P. (2004). Improving the design of knowledge transfer strategies by understanding farmer attitudes and behaviour. Journal of Farm Management 12:17–32.Google Scholar
Gyau, A., Takoutsing, B., Degrande, A. and Franzel, S. (2012). Producers’ motivation for collective action for kola production and marketing in Cameroon. Journal of Agriculture and Rural Development in the Tropics and Subtropics 113:43–50.Google Scholar
Keil, A., Zeller, M. and Franzel, S. (2005). Improved tree fallows in smallholder maize production in Zambia: Do initial testers adopt the technology? Agroforestry Systems 64:225–236.Google Scholar
Läpple, D. and Van Rensburg, T. (2011). Adoption of organic farming: Are there differences between early and late adoption? Ecological Economics 70:1406–1414.CrossRefGoogle Scholar
Martinez-Garcia, C. G. (2011). Factors influencing adoption of crop and forage related and animal husbandry technologies by small-scale dairy farmers in the highlands of central Mexico. Ph.D. Thesis degree. School of Agriculture, Policy and Development, The University of Reading, UK.Google Scholar
Martínez-García, C. G., Dorward, P. and Rehman, T. (2012). Farm and socioeconomic characteristics of small-holder milk producers and their influence on the technology adoption in Central Mexico. Tropical Animal Health and Production 44:1199–1211.Google Scholar
Martínez-García, C. G., Dorward, P. and 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 Science 152:228–238.Google Scholar
Martínez-García, C. G., Dorward, P. and Rehman, T. (2015). Factors influencing adoption of crop and forage related and animal husbandry technologies by small-scale dairy farmers in Central Mexico. Experimental Agriculture 52:87–109.CrossRefGoogle Scholar
McKemey, K. and Rehman, T. (2002). The theory of reasoned action and its applications. Document 01/02. School of Agriculture, Policy and Development, University of Reading. UK.Google Scholar
Rehman, T., McKemey, K., Yates, C. M., Cooke, R. J., Garforth, C. J., Tranter, R. B., Park, J. R. and Dorward, P. T. (2007). Identifying and understanding factors influencing the uptake of new technologies on dairy farms in SW England using the theory of reasoned action. Agricultural Systems 94:281–293.Google Scholar
SIAP (2012). Servicio de Información Agroalimentaria y Pesquera. http://www.siap.gob.mx/index.php?option=com_wrapper&view=wrapper&Itemid=373 (accessed 11.06.2012).Google Scholar
Somda, J., Kamuanga, M. and Tollens, E. (2005). Characteristics and economic viability of milk production in the smallholder farming systems in the Gambia. Agricultural Systems 85:42–58.CrossRefGoogle Scholar
Staal, S. J., Baltenweck, I., Waithaka, M. M., Wolff, T. D. and Njoroge, L. (2002). Localization and uptake: Integrated households and GIS analysis of technology adoption and land use, with application to smallholder dairy farms in Kenya. Agricultural Economics 27:295–315.Google Scholar
Vogt, W. P. and Burke, J. R. (2011). Dictionary of Statistics and Methodology: A Non-Technical Guide for the Social Sciences, 4th edn. USA: Sage publications.Google Scholar
Zubair, M. and Garforth, C. (2006). Farm level tree planting in Pakistan: The role of farmers’ perceptions and attitudes. Agroforestry Systems 66:217–229.Google Scholar
Supplementary material: Image

Martínez-García supplementary material

Figure S1

Download Martínez-García supplementary material(Image)
Image 259 KB
Supplementary material: Image

Martínez-García supplementary material

Figure S2

Download Martínez-García supplementary material(Image)
Image 96.6 KB
Supplementary material: File

Martínez-García supplementary material

Table S1

Download Martínez-García supplementary material(File)
File 22.6 KB