Underlying Constructs of Farmers’ Perceptions towards Bt Cotton Among Former Cotton Farmers in Northern Ghana: Empirical Application of Q Methodology
Subject Areas : Information Technology in Agriculture
1 - Department of Agricultural Extension, Rural Development & Gender Studies
Faculty of Agribusiness of the University for Development Studies, Tamale
Post office Box TL 1882, Tamale, Ghana
Keywords: perceptions, narratives, Bt cotton, constructs and dimensions,
Abstract :
It is often argued that learning from best examples in the neighbouring Burkina Faso and elsewhere, Ghana can succeed in revamping the collapsing cotton industry by introducing Bt cotton to farmers. This paper therefore presents a survey findings on farmers’ views and perceptions towards the possible introduction of Bt cotton. A stratified random sampling techniques was applied in selecting 254 farmers from the four cotton producing zones in northern Ghana and Q methodology adopted in collecting narratives and perceptions towards Bt cotton. Principal Components Analysis (PCA) was applied in extracting the underlying constructs from farmers’ narratives on Bt cotton. The extraction method was guided by Kaiser’s Eigenvalue-greater-than-one rule follow by Parallel analysis method of Monte Carlo and Scree test techniques. Results of the PCA identified five broad issues representing farmers’ views about the introduction of Bt cotton. The broad issues explaining farmers’ views and perception towards Bt cotton are ‘contractual issues with cotton companies’, ‘issues relating to problems and challenges in cotton farming’, ‘issues relating to farmers desire to go back to cotton farming’, ‘positive views on Bt cotton’ and ‘some reservations on Bt cotton’. This paper therefore recommends that for government and other stakeholders to succeed in revamping the cotton industry, there is the need for farmers’ concerns on contractual issues to be addressed and for more information on Bt cotton to be provided to resolve the reservation farmers have about Bt cotton.
Ashitey E. (2013). Ghana Agricultural Biotechnology Annual Report. Global Agriculture Information Network. USDA Foreign Agricultural Services.
Baquedano, F. G., Sanders, J. H., Vitale, J. (2010). Increasing incomes of Malian cotton farmers: Is elimination of US subsidies the only solution? Agric Syst, 103, 418-432.
Bartlett, M. S. (1950).Tests of significance in factor analysis. British Journal of Psychology. 3 (2):77-85.
Brookes, G. and Barfoot, P. (2015). GM crops: global socio-economic and environmental impacts 1996-2013. PG Economics Ltd 2015.
Choudhary, B. and Gaur, K. (2015). Biotech Cotton in India, 2002 to 2014. ISAAA Series of Biotech Crop Profiles. ISAAA: Ithaca, NY.
Costello, A. B and Osborne, J. W. (2005). Best Practices in Exploratory Factor Analysis: Four Recommendations for Getting the Most from Your Analysis. Practical Assessment, Research & Evaluation. 2005; 10(7):1-9.
Tschirley, D, L., Poulton, C., Gergely, N., Labaste, P., Baffes, J., Boughton, D and Estur, G. (2010). Institutional Diversity and Performance in African Cotton Sectors. Development Policy Review, 2010, 28 (3): 295-323.
Davis, C. H and Michelle, C. (2011). Q Methodology in Audience Research: Bridging the Qualitative/Quantitative ‘Divide’? Participation journal of audience & reception studies, pp. 527-561.
FAO STAT. (2016). Cotton Production from 1993 to 2013. Food and Agriculture Organization of the United Nations Statistics Division (available on: http://faostat3.fao.org/browse/Q/QC/E accessed on 6/2/2016)
GNA. (2015). National Biosafety Authority board inaugurated. 17 February 2015 21:10 (Available online at:https://www.modernghana .com/news/599250/1/national-biosafety-authority-board-inaugurated.html retrieved on 20th February, 2016)
GSS. (2010). Population and Housing Census. Ghana Statistical Service (GSS), GOG, Accra.
GSS. (2014). Ghana Living Standard Survey Round six: Main Report. Ghana Statistical Service GOG, August, 2014, Accra.
Hair, J., Anderson, R. E., Tatham, R. L., Black, W. C. (1995). Multivariate data analysis. 4th ed. New Jersey: Prentice-Hall Inc; 1995.
Henson, R. K., Roberts, J. K. (2006). Use of Exploratory Factor Analysis in Published Research: Common Errors and Some Comment on Improved Practice. Educational and Psychological Measurement. 66(3): 393-416.
Hogarty, K., Hines, C., Kromrey, J., Ferron, J and Mumford, K. (2006). The Quality of Factor Solutions in Exploratory Factor Analysis: The Influence of Sample Size, Communality, and Over determination. Educational and Psychological Measurement. 65(2):202-26.
James, C. (2011). Global Status of commercialized Biotech/GM crops. International Services for Acquisition of Agrobiotechnology Application, ISAAA.
James, C. (2014). Global Status of Commercialized Biotech/GM Crops: 2014. ISAAA Brief No. 49. ISAAA: Ithaca, New York.
Jolliffe I. T. (2002). Principal Component Analysis. Springer Series in Statistics. ISBN: 978-0-387-95442-4 (Print) 978-0-387-22440-4 (Online)
Kaiser, H. F. (1970). A Second-Generation Little Jiffy. Psychometrika. 1970;: 35(4):401-15.
Kaiser, H. F., Jiffy, L and Mark, I. V. (1974). Journal of Educational and Psychological Measurement, 34, 1, 111-117.
NORC (National Opinion Research Center). (2011). Cross country comparison of key indicators from COMPACI / CmiA Baseline Surveys.
Peltzer, R and Röttger, D. (2013). Cotton sector organization models and their impact on farmer’s productivity and income. Discussion Paper /Germany Development Institute (Deutsches Institut für Entwicklungspolitik) ISSN 1860-0441 ISBN 978-3-88985-627-2.
Pett, M. A, Lackey, N. R and Sullivan, J. J. (2003). Making Sense of Factor Analysis: The use of factor analysis for instrument development in health care research. California: Sage Publications Inc; 2003.
Philippe, S., Mpoko, B., & Kjell S. (2011). Revitalizing the Ghanaian Cotton Sector. A background paper for discussion, 2011, pp: 4-8.
Poulton, C., Gibbon, P., Hanyani-Mlambo, B., Kydd, J., Maro, W., Nylandsted Larsen, M., Osorio, A., Tschirley, D. and Zulu, B. (2004). Competition and Co-ordination in Liberalized African Cotton Market Systems’, World Development, 32 (3): 519-36
Purnamita, D and Bhaskar, V. (2004). Adapting Q-methodology to investigate stakeholder perceptions in participatory forestry in India. Submission for ISEE Montreal 2004.
Ledesma, R and Valero-Mora, P. (2007). Determining the Number of Factors to Retain in EFA: an easy-touse computer program for carrying out Parallel Analysis. Practical Assessment, Research & Evaluation Journal. 12(2): 1-11.
Saheed, M. (2014). An Assessment of Q Methodology for Social Research. A study project submitted to Brandenburg University of Technology for the Degree of MSc.
Stephenson, W. (1935). Correlating persons instead of tests. Character and Personality, 4: 17-24.
Tabachnick, B. G and Fidell, L. S. (2007). Using Multivariate Statistics. Boston: Pearson Education Inc.
Teft, J. (2004). Building on Successes in African Agriculture Mali’s White Revolution: Smallholder Cotton From 1960 to 2003; International Food Policy Research Institute Policy Brief: Washington, DC, USA, 2004.
Thompson, B and Daniel, L. G. (1996). Factor analytic evidence for the construct validity of scores: A historical overview and some guidelines. Educational and Psychological Measurement. 56(2):197-208.
Vitale, J., Ouattarra, M and Vognan, G. (2011). Enhancing Sustainability of Cotton Production Systems in West Africa: A Summary of Empirical Evidence from Burkina Faso. J. Sustain. 3: 1136-1169.
Vitale, J. D. (2010). The Commercial Application of GMO Crops in Africa: Burkina Faso’s Decade of Experience with Bt Cotton. AgBioForum, 13(4): 320-332.
Vitale, J., Ouattarra , M. and Vognan G. (2011). Enhancing Sustainability of Cotton Production Systems in West Africa: A Summary of Empirical Evidence from Burkina Faso. Sustainability 2011, 3, 1136-1169.
Vognan, G., Ouédraogo, M and Ouédraogo, S. (2002). Description of the Cotton System in the Burkina Faso Region. Intermediary Report]; Institut de l’Environnement et de Recherches Agricoles (INERA): Bobo Dialasso, Burkina Faso.
Williams, B., Brown, T., & Onsman, A. (2010). Exploratory factor analysis: A five-step guide for novices. Australasian Journal of Paramedicine, 8(3). Retrieved from http://ro.ecu.edu.au/jephc /vol8/iss3/1 (accessed on December, 2015).