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The use of SWOT analysis to explore and prioritize conservation and development strategies for local cattle breeds

Published online by Cambridge University Press:  20 December 2012

D. Martín-Collado ,
C. Díaz ,
A. Mäki-Tanila ,
F. Colinet ,
D. Duclos ,
S. J. Hiemstra ,
G. Gandini  and
EURECA Consortium
D. Martín-Collado
Affiliation:
Departamento de Mejora Genética Animal, INIA, Ctra. de La Coruña km 7.5, 28040 Madrid, Spain
C. Díaz*
Affiliation:
Departamento de Mejora Genética Animal, INIA, Ctra. de La Coruña km 7.5, 28040 Madrid, Spain
A. Mäki-Tanila
Affiliation:
MTT Agrifood Research Finland, 31600 Jokioinen, Finland
F. Colinet
Affiliation:
Animal Science Unit, Gembloux Agro-Bio Tech, University of Liege, 5030 Gembloux, Belgium
D. Duclos
Affiliation:
Institut de l'Elevage, Cryobanque Nationale, 75595 Paris, Cedex 12, France
S. J. Hiemstra
Affiliation:
Centre for Genetic Resources, Wageningen University and Research Centre, 8200 AB, Lelystad, The Netherlands
G. Gandini
Affiliation:
Department VSA, Faculty of Veterinary, University of Milan, 20133 Milan, Italy
*
†E-mail: cdiaz@inia.es
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Abstract

SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis is a tool widely used to help in decision making in complex systems. It suits to exploring the issues and measures related to the conservation and development of local breeds, as it allows the integration of many driving factors influencing breed dynamics. We developed a quantified SWOT method as a decision-making tool for identification and ranking of conservation and development strategies of local breeds, and applied it to a set of 13 cattle breeds of six European countries. The method has four steps: definition of the system, identification and grouping of the driving factors, quantification of the importance of driving factors and identification and prioritization of the strategies. The factors were determined following a multi-stakeholder approach and grouped with a three-level structure. Animal genetic resources expert groups ranked the factors, and a quantification process was implemented to identify and prioritize strategies. The proposed SWOT methodology allows analyzing the dynamics of local cattle breeds in a structured and systematic way. It is a flexible tool developed to assist different stakeholders in defining the strategies and actions. The quantification process allows the comparison of the driving factors and the prioritization of the strategies for the conservation and development of local cattle breeds. We identified 99 factors across the breeds. Although the situation is very heterogeneous, the future of these breeds may be promising. The most important strengths and weaknesses were related to production systems and farmers. The most important opportunities were found in marketing new products, whereas the most relevant threats were found in selling the current products. The across-breed strategies utility decreased as they gained specificity. Therefore, the strategies at European level should focus on general aspects and be flexible enough to be adapted to the country and breed specificities.

Keywords

quantified SWOTanimal genetic resources conservationmulti-stakeholder approachstrategy developmentlocal breed
Type
Breeding and genetics
Information
animal , Volume 7 , Issue 6 , June 2013 , pp. 885 - 894
Copyright
Copyright © The Animal Consortium 2012

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Footnotes

‡

http://www.regionalcattlebreeds.eu

References

Alderson, S 2003. Animal genetic resources and sustainable livelihood. Ecological Economics 45, 331–339.Google Scholar
Drucker, A, Gomez, V, Anderson, S 2001. The economic valuation of farm animal genetic resources: a survey of available methods. Ecological Economic 36, 1–18.Google Scholar
Food and Agriculture Organization of the United Nations (FAO) 2007. The state of the world's animal genetic resources for food and agriculture. FAO, Rome, Italy.Google Scholar
FAO 2010. Breeding strategies for sustainable management of animal genetic resources. FAO, Rome, Italy.Google Scholar
Fimland, E, Oldenbroek, K 2007. Practical implications of utilization and management. In Utilization and conservation of farm animal genetic resources (ed. K Oldenbroek), pp. 195–213. Wageningen Academic Publishers, Wageningen, The Netherlands.Google Scholar
Gable, GG, Lee, JN, Kwahk, KY, Green, P 2007. Administrative placement of the information systems academic discipline: a comparative SWOT analysis. Communications of the Associations for Information Systems 21, 137–165.Google Scholar
Gandini, G, Villa, E 2003. Analysis of the cultural value of livestock breeds: a methodology. Journal of Animal Breeding and Genetics 120, 1–11.Google Scholar
Gandini, G, Martín-Collado, D, Colinet, F, Duclos, D, Hiemstra, SJ, Sooini, K, EURECA Consortium, Díaz, C 2012. Farmer's views and values to focus on cattle conservation policies: the case of eight European Countries. Journal of Animal Breeding and Genetics 129, 427–435.Google Scholar
Groeneveld, LF, Lenstra, JA, Eding, H, Toro, MA, Scherf, B, Pilling, D, Negrini, R, Finlay, EK, Jianlin, H, Groeneveld, E, Weigend, S, , The GLOBALDIV Consortium 2010. Genetic diversity in farm animals – a review. Animal Genetics 41, 6–31.Google Scholar
Hill, T, Westbrook, R 1997. SWOT analysis: it's time for a product recall. Long Range Planning 30, 46–52.Google Scholar
Impoinvil, DE, Ahmad, S, Troyo, A, Keating, J, Githeko, AK, Mbogo, CM, Kibe, L, Githure, JI, Gad, AM, Hassan, AN, Orshan, L, Warburg, A, Calderón-Arguedas, O, Sánchez-Loria, VM, Velit-Suarez, R, Chadee, DD, Novak, RJ, Beier, JC 2007. Comparison of mosquito programs in seven urban sites in Africa, the Middle East and the Americas. Health Policy 83, 196–212.Google Scholar
Kajanus, M, Kangas, J, Kurttila, M 2004. The use of value focused thinking and the A'WOT hybrid method in tourism management. Tourism Management 25, 499–506.Google Scholar
Kangas, J, Kurttila, M, Kajanus, M, Kangas, A 2003. Evaluating the management strategies of a forestland state – the S-O-S approach. Journal of Environmental Management 69, 349–358.Google Scholar
Karppi, I, Kokkonen, M, Lähteenmäki-Smith, K 2001. SWOT-analysis as a basis for regional strategies. Working Paper 2001, 4. Nordregio-Nordic Centre for Spatial Development, Stockholm, Sweden.Google Scholar
Kurttila, M, Pesonen, M, Kangas, J, Kajanus, J 2000. Utilizing the analytic hierarchy process (AHP) in SWOT analysis – a hybrid method and its applications to a forest-certification case. Forest Policy and Economics 1, 41–52.Google Scholar
Lee, KL, Huang, WC, Teng, JY 2009. Locating the competitive relation of global logistics hub using quantitative SWOT analytical method. Quality & Quantity 43, 87–107.Google Scholar
Rege, JEO, Gibson, JP 2003. Animal genetic resources and economic development: issues in relation to economic valuation. Ecological Economic 45, 319–330.Google Scholar
Saaty, TL 1986. Axiomatic foundation of the analytic hierarchy process. Management Science 32, 843–855.Google Scholar
Saaty, TL 2008. Decision making with the analytic hierarchy process. International Journal of Service Sciences 1, 83–98.Google Scholar
Saaty, TL, Takizawa, M 1986. Dependence and independence: from linear hierarchies to nonlinear networks. European Journal of Operational Research 26, 229–237.Google Scholar
Tisdell, C 2003. Socioeconomic causes of loss of animal genetic diversity: analysis and assessment. Ecological Economics 45, 365–376.Google Scholar
Vonk, G, Geertman, S, Schot, P 2007. A SWOT analysis of planning support systems. Environmental and Planning A 39, 1699–1714.Google Scholar
Weihrich, H 1989. The TOWS matrix – a tool for situational analysis. Long Range Planning 15, 54–66.Google Scholar
Yüksel, I, Dagdeviren, M 2007. Using the analytic network process (ANP) in a SWOT analysis – a case study for a textile firm. Information Sciences 177, 3364–3382.Google Scholar
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