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Cited by 73Cognitive Science and MappingClimate change impacts on agricultureDisaster Management and Resilience

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Application of Fuzzy Cognitive Mapping in Livelihood Vulnerability Analysis

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Murungweni, Chrispen, van Wijk, Mark T., Andersson, Jens A., Smaling, Eric M. A., Giller, Ken E.·2011·Ecology and Society
DOI 10.5751/es-04393-160408
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Abstract

Murungweni, C., M. T. Van Wijk, J. A. Andersson, E. M. A. Smaling, and K. E. Giller. 2011. Application of fuzzy cognitive mapping in livelihood vulnerability analysis. Ecology and Society 16(4): 8. https://doi.org/10.5751/ES-04393-160408

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  • FCM has been used with a wide variety of individuals, including illiterate persons and indigenous groups, to explore causes of complex phenomena.

    “It has been used with a wide variety of individuals, including illiterate persons and indigenous groups, to explore the causes of a variety of complex phenomena, including short birth intervals, disaster preparedness and risk reduction, satisfaction of care amongst HIV patients, maternal health, and livelihood vulnerability (Murungweni et al., 2011;Sarmiento et al., 2022;Sarmiento et al., 2020;”

    From Sexual and gender-based violence against South Sudanese refugees in Uganda: a mixed-methods study (2025) · cites this paper as Murungweni et al., 2011

    The ‘Application of fuzzy cognitive maps’ and ‘Utility of fuzzy cognitive maps in livelihood analysis’ sections describe using FCMs with local people and stakeholders to examine interacting causes of livelihood vulnerability. Our copy does not establish that participants were illiterate or indigenous, or that this paper used FCMs across the other phenomena listed in the multi-citation sentence. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 38

  1. Adger, W. N. 1999. Social vulnerability to climate change and extremes in coastal Vietnam. World Development 27 (2):249-269.
  2. Adger, W. N. 2000. Social and ecological resilience: are they related? Progress in Human Geography 24(3):347-364. http:/ /dx.doi.org/10.1191/030913200701540465 · DOI
  3. Axelrod, R., editor. 1976. Structure of decision: the cognitive maps of political elites. Princeton University Press, Princeton, New Jersey, USA.
  4. Berkes, F. 2007. Understanding uncertainty and reducing vulnerability: lessons from resilience thinking. Natural Hazards 41(2):283-295. http://dx.doi.org/10.1007/s11069-00 6-9036-7 · DOI
  5. Carley, K., and M. Palmquist. 1992. Extracting, representing, and analyzing mental models. Social Forces 70(3):601-636. http://dx.doi.org/10.2307/2579746 · DOI
  6. Castella, J.-C., Tran Ngoc Trung, and S. Boissau. 2005. Participatory simulation of land-use changes in the northern mountains of Vietnam: the combined use of an agent-based model, a role-playing game, and a geographic information system. Ecology and Society 10(1): 27. [online] URL: http:// www.ecologyandsociety.org/vol10/iss1/art27/.
  7. Cooper, G. F. 1990. The computational complexity of probabilistic inference using Bayesian belief networks. Artificial Intelligence 42(2-3):393-405. http://dx.doi.org/10.1 016/0004-3702(90)90060-D Crome, F. H. J., M. R. Thomas, and L. A. Moore. 1996. A novel Bayesian approach to assessing impacts of rain forest logging. Ecological Applications 6(4):1104-1123. http://dx.d oi.org/10.2307/2269595 · DOI
  8. Cumming, D. H. M. 2005. Wildlife, livestock and food security in the southeast lowveld of Zimbabwe. Pages 41-46
  9. Dougill, A. J., E. D. G. Fraser, and M. S. Reed. 2010. Anticipating vulnerability to climate change in dryland pastoral systems: using dynamic systems models for the Kalahari. Ecology and Society 15(2): 17. [online] URL: http: //www.ecologyandsociety.org/vol15/iss2/art17/.
  10. Dzingirai, V. 2003. The new scramble for the African countryside. Development and Change 34(2):243-264. http:// dx.doi.org/10.1111/1467-7660.00304 · DOI
  11. Eakin, H., and A. L. Luers. 2006. Assessing the vulnerability of social-environmental systems. Annual Review of Environment and Resources 31:365-394. http://dx.doi.org/10 .1146/annurev.energy.30.050504.144352 · DOI
  12. Folke, C. 2006. Resilience: the emergence of a perspective for social-ecological systems analyses. Global Environmental Change 16(3):253-267. http://dx.doi.org/10.1016/j.gloenvcha .2006.04.002 · DOI · Paper page
  13. Folke, C., S. Carpenter, T. Elmqvist, L. Gunderson, C. S. Holling, and B. Walker. 2002. Resilience and sustainable development: building adaptive capacity in a world of transformations. Ambio 31(5):437-440.
  14. Fraser, E. D. G. 2007. Travelling in antique lands: using past famines to develop an adaptability/resilience framework to identify food systems vulnerable to climate change. Climatic Change 83(4):495-514. http://dx.doi.org/10.1007/s10584-007 -9240-9 · DOI
  15. Haas, T. C. 1991. Partial validation of Bayesian belief network advisory systems. AI Applications 5(4):59-71.
  16. Heckerman, D. 1999. A tutorial on learning with Bayesian networks. In M. I. Jordan, editor. Learning in graphical models. MIT Press, Cambridge, Massachusetts, USA. http://d x.doi.org/10.1007/978-3-540-85066-3_3 · DOI
  17. Hermann, M. G. 1978. Review: political theory and methodology. American Political Science Review 72:1017-1018. http://dx.doi.org/10.2307/1955121 · DOI
  18. Janssen, M. A., M. L. Schoon, W. Ke, K. Börner. 2006. Scholarly networks on resilience, vulnerability and adaptation within the human dimensions of global environmental change. Global Environmental Change 16(3):240-252. http://dx.doi.o rg/10.1016/j.gloenvcha.2006.04.001 · DOI
  19. Kinsey, B., K. Burger, and J. W. Gunning. 1998. Coping with drought in Zimbabwe: survey evidence on responses of rural Ecology and Society 16(4): 8 http://www.ecologyandsociety.org/vol16/iss4/art8/ households to risk. World Development 26(1):89-110. http://d x.doi.org/10.1016/S0305-750X(97)00124-1 · DOI
  20. Kok, K. 2009. The potential of fuzzy cognitive maps for semi- quantitative scenario development, with an example from Brazil. Global Environmental Change 19(1):122-133. http://d x.doi.org/10.1016/j.gloenvcha.2008.08.003 · DOI
  21. Kosko, B. 1986. Fuzzy cognitive maps. International Journal of Man-Machine Studies 24(1):65-75. http://dx.doi.org/10.1016/ S0020-7373(86)80040-2 · DOI · Paper page
  22. Martínez-Santos, P., H. J. Henriksen, P. Zorrilla, and P. E. Martínez-Alfaro. 2010. Comparative reflections on the use of modelling tools in conflictive water management settings: the Mancha Occidental aquifer, Spain. Environmental Modelling & Software 25(11):1439-1449. http://dx.doi.org/10.1016/j.en vsoft.2008.11.011 · DOI
  23. Mendoza, G. A., and R. Prabhu. 2006. Participatory modeling and analysis for sustainable forest management: overview of soft system dynamics models and applications. Forest Policy and Economics 9(2):179-196.
  24. Newton, A. C., E. Marshall, K. Schreckenberg, D. Golicher, D. W. te Velde, F. Edouard, and E. Arancibia. 2006. Use of a Bayesian belief network to predict the impacts of commercializing non-timber forest products on livelihoods. Ecology and Society 11(2): 24. [online] URL: http://www.eco logyandsociety.org/vol11/iss2/art24/.
  25. Nyamudeza. 1999. Agronomic practices for the low rainfall natural regions of Zimbabwe. Pages 49-63 in E. Manzungu, A. Senzanje, and P. van der Zaag, editors. Water for agriculture in Zimbabwe: policy and management options for the smallholder sector. University of Zimbabwe Publications, Harare, Zimbabwe.
  26. O'Sullivan, D., and M. Haklay. 2000. Agent-based models and individualism: Is the world agent-based? Environment and Planning A 32(8):1409-1425. http://dx.doi.org/10.1068/a32140 · DOI
  27. Özesmi, U., and S. L. Özesmi. 2004. Ecological models based on people's knowledge: a multi-step fuzzy cognitive mapping approach. Ecological Modelling 176(1-2):43-64. http://dx.doi. org/10.1016/j.ecolmodel.2003.10.027 · DOI
  28. Pearl, J. 1993. Belief networks revisited. Artificial Intelligence 59(1-2):49-56. http://dx.doi.org/10.1016/0004-3702(93)90169- C Rattray, J. M., R. M. M. Cormack, and R. R. Staples. 1953. The vlei areas of S. Rhodesia and their uses. Rhodesia Agricultural Journal 50:465-483. · DOI
  29. Scoones, I. 2009. Livelihoods perspectives and rural development. Journal of Peasant Studies 36(1):171-196. http ://dx.doi.org/10.1080/03066150902820503 · DOI
  30. Smid, J. H., D. Verloo, G. C. Barker, and A. H. Havelaar. 2010. Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment. International Journal of Food Microbiology 139 (Supplement):S57-S63. http://dx.doi.org/10.1016/j.ijfoodmic ro.2009.12.015 · DOI
  31. Spenceley, A. 2008. Requirements for sustainable nature- based tourism in transfrontier conservation areas: a southern African Delphi consultation. Tourism Geographies 10 (3):285-311. http://dx.doi.org/10.1080/14616680802236295 Subcommittee on Disaster Reduction. 2003. Reducing disaster vulnerability through science and technology. National Science and Technology Council, Washington, D. C., USA. [online] URL: http://www.sdr.gov/SDR_Report_Re ducingDisasterVulnerability2003.pdf. · DOI
  32. Swendsen, J. D., and S. Norman. 1998. Preparing for community violence: mood and behavioral correlates of the second Rodney King verdicts. Journal of Traumatic Stress 11 (1):57-70. http://dx.doi.org/10.1023/A:1024405132015 · DOI
  33. Toner, A. 2003. Exploring sustainable livelihoods approaches in relation to two interventions in Tanzania. Journal of International Development 15(6):771-781. http://dx.doi.org/1 0.1002/jid.1030 · DOI
  34. Turner, B. L. II, R. E. Kasperson, P. A. Matson, J. J. McCarthy, R. W. Corell, L. Christensen, N. Eckley, J. X. Kasperson, A. Luers, M. L. Martello, C. Polsky, A. Pulsipher, and A. Schiller. 2003. A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences 100 (14):8074-8079. http://dx.doi.org/10.1073/pnas.1231335100 · DOI
  35. Van Vliet, M., K. Kok, and T. Veldkamp. 2010. Linking stakeholders and modellers in scenario studies: the use of fuzzy cognitive maps as a communication and learning tool. Futures 42(1):1-14. http://dx.doi.org/10.1016/j.futures.2009.08.005 · DOI
  36. Watts, M. J., and H. G. Bohle. 1993. The space of vulnerability: the causal structure of hunger and famine. Progress in Human Geography 17(1):43-67. http://dx.doi.org/10.1177/03091325 9301700103 · DOI
  37. Weinreb, G. E., T. C. Elston, and K. Jacobson. 2006. Causal mapping as a tool to mechanistically interpret phenomena in cell motility: application to cortical oscillations in spreading cells. Cell Motility and the Cytoskeleton 63(9):523-532. http: //dx.doi.org/10.1002/cm.20143 · DOI
  38. Wolfson, L. J., J. B. Kadane, and M. J. Small. 1996. Bayesian environmental policy decisions: two case studies. Ecological Applications 6(4):1056-1066. http://dx.doi.org/10.2307/2269590 · DOI

Cited by

Sorted by citations

Metadata

Authors
Murungweni, C., van Wijk, M. T., Andersson, J. A., Smaling, E. M. A., & Giller, K. E.
Affiliations
Wageningen University & Research (NL)
ORCID
Venue
Ecology and Society
Publisher
Resilience Alliance, Inc.
Published
2011
Volume
16
Issue
4
ISSN
1708-3087 (ISSN-L)
DOI
10.5751/es-04393-160408
OpenAlex
W2058511155
Cited by
73
References
2
Citations by year
2026: 2 · 2025: 1 · 2024: 3 · 2023: 7 · 2022: 3 · 2021: 5 · 2020: 6 · 2019: 8 · 2018: 2 · 2017: 2 · 2016: 7 · 2015: 10 · 2014: 9 · 2013: 5 · 2012: 2
FWCI
5.01
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Ecology and Society (publishedVersion, cc-by)
  • University of Twente Research Information (publishedVersion, other-oa)
  • Socio-Environmental Systems Modeling (acceptedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Digital Library Of The Commons Repository (Indiana University) (submittedVersion)
  • University of Twente Research Information (submittedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Cognitive Science and Mapping
  • Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Climate change impacts on agriculture
  • Social Sciences › Sociology and Political Science › Disaster Management and Resilience
Keywords
fuzzy cognitive mapping, livelihood vulnerability, vulnerability assessment, livelihood systems, social-ecological systems, participatory modeling

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