#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Evaluating poverty alleviation strategies in a developing country


Autoři: Pramod K. Singh aff001;  Harpalsinh Chudasama aff001
Působiště autorů: Institute of Rural Management Anand (IRMA), Anand, Gujarat, India aff001
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0227176

Souhrn

A slew of participatory and community-demand-driven approaches have emerged in order to address the multi-dimensional nature of poverty in developing nations. The present study identifies critical factors responsible for poverty alleviation in India with the aid of fuzzy cognitive maps (FCMs) deployed for showcasing causal reasoning. It is through FCM-based simulations that the study evaluates the efficacy of existing poverty alleviation approaches, including community organisation based micro-financing, capability and social security, market-based and good governance. Our findings confirm, to some degree, the complementarity of various approaches to poverty alleviation that need to be implemented simultaneously for a comprehensive poverty alleviation drive. FCM-based simulations underscore the need for applying an integrated and multi-dimensional approach incorporating elements of various approaches for eradicating poverty, which happens to be a multi-dimensional phenomenon. Besides, the study offers policy implications for the design, management, and implementation of poverty eradication programmes. On the methodological front, the study enriches FCM literature in the areas of knowledge capture, sample adequacy, and robustness of the dynamic system model.

Klíčová slova:

Centrality – Cognition – Finance – Health care policy – Social cognition – Welfare (social security) – economic growth – Economics of poverty


Zdroje

1. World Bank. The World Bank: Annual Report 2015. The World Bank, Washington, DC, USA. 2015.

2. Sen AK. Poverty: an ordinal approach to measurement. Econometrica. 1976;44(2):219–231.

3. Sen AK. A sociological approach to the measurement of poverty: a reply to Professor Peter Townsend. Oxford Economic Papers, New Series. 1985a;37(4):669–676.

4. Sen AK. Social exclusion: concept, application, and scrutiny. Social Development Papers No. 1. 2000. Office of Environment and Social Development, Asian Development Bank. Manila, Philippines. ISBN: 971-561-274-1.

5. UNDP. Eradicate extreme poverty and hunger: where do we stand? The United Nations Development Programme (UNDP), New York, USA. 2014.

6. United Nations. Transforming our world: the 2030 Agenda for Sustainable Development. The UN General Assembly, A/RES/70/1. 2015. Available at: https://www.refworld.org/docid/57b6e3e44.html

7. Chakrabarti A, Dhar A. Social funds, poverty management and subjectification: beyond the World Bank approach. Cambridge Journal of Economics. 2013;37(5):1035–1055. doi: 10.1093/cje/bes077

8. Yalegama S, Chileshe N, Ma T. Critical success factors for community-driven development projects: A Sri Lankan community perspective. International Journal of Project Management. 2016;34:643–659. doi: 10.1016/j.ijproman.2016.02.006

9. Bhagwati J, Panagariya A. Reforms and economic transformation in India. Series: Studies in Indian Economic Policies. New York: Oxford University Press. 2012. ISBN:978–0–19–991520–0.

10. Growth Ambarkhane D. and poverty reduction as complimentary processes an approach to inclusive growth. Journal of Commerce & Management Thought. 2013;4(4):904–921. ISSN (Online):0976-478X.

11. Bank World. World Development Report 2000/2001: Attacking Poverty. World Development Report. Oxford University Press. New York, Washington, DC, USA. 2001.

12. Lashley JG. Micro-finance and poverty alleviation in the Caribbean: a strategic overview. Journal of Microfinance. 2004;6(1):83–94.

13. Mwenda KK, Muuka GN. Towards best practices for micro finance institutional engagement in African rural areas: selected cases and agenda for action. International Journal of Social Economics. 2004;31(1/2):143–158. doi: 10.1108/03068290410515475

14. Akanji OO. Micro-finance as a strategy for poverty reduction: Review of the country’s experiences of finance programs for the poor. Central Bank of Nigeria (CBN) Economic & Financial Review. 2006;39(4). doi: 10.1016/j.dib.2018.08.191

15. World Bank. Finance for all? Policies and pitfalls in expanding access. World Bank Policy Research Report. The World Bank, Washington, DC, USA. 2007.

16. Imai KS, Arun T, Annim SK. Micro-finance and household poverty reduction: new evidence from India. World Development. 2010;38(12):1760–1774. doi: 10.1016/j.worlddev.2010.04.006

17. Nawaz S. Micro-finance and poverty reduction: evidence from a village study in Bangladesh. Journal of Asian and African Studies. 2010;45(6):670–683. doi: 10.1177/0021909610383812 21174878

18. Durrani MKK, Usman A, Malik MI, Ahmad S. Role of micro-finance in reducing poverty: a look at social and economic factors. International Journal of Business and Social Science. 2011;2(21):138–144.

19. Montgomery H, Weiss J. Can commercially-oriented microfinance help meet the millennium development goals? Evidence from Pakistan. World Development. 2011;39(1):87–109. doi: 10.1016/j.worlddev.2010.09.001

20. Okibo BW, Makanga N. Effects of micro-finance institutions on poverty reduction in Kenya. International Journal of Current Research and Academic Review. 2014;2(2):76–95. ISSN: 2347–3215.

21. Banerjee SB, Jackson L. Micro-finance and the business of poverty reduction: critical perspectives from rural Bangladesh. Human Relations. 2017;70(1):63–91. doi: 10.1177/0018726716640865

22. Wright GAN. Micro-finance Systems: designing quality financial services for the poor. Zed Books Ltd. London & New York, USA, and The University Press Limited, Dhaka, Bangladesh. 2000.

23. Khandker SR. Micro-finance and poverty: data from Bangladesh. World Bank Economic Review. 2005;19(2):263–286. doi: 10.1093/wber/1hi008

24. Westover J. The record of micro-finance: the effectiveness/ineffectiveness of microfinance programs as a means of alleviating poverty. Electronic Journal of Sociology. 2008. Available at: http://www.sociology.org/ejs-archives

25. Das SK, Bhowal A. Impact of self-help group on members and its involvement in social issues: core vs. peripheral issues. International Journal of Business and Management Invention 2013;2(12):48–72. ISSN (Online):2319–8028.

26. Arora S, Romijn H. The empty rhetoric of poverty reduction at the base of the pyramid. Organization. 2012;19(4):481–505. doi: 10.1177/1350508411414294

27. Sen AK. Commodities and capabilities. Oxford, Elsevier Science Publishers. Amsterdam, North-Holland. 1985b.

28. Sen AK. Capability and well-being. In: Nussbaum MC, Sen AK, editors. The Quality of Life: Oxford, Clarendon Press; 1993. pp. 30–53.

29. Robeyns I. The capability approach: a theoretical survey. Journal of Human Development. 2005;6(1):93–114. doi: 10.1080/146498805200034266

30. Nguyen TC, Rieger M. Community-driven development and social capital: evidence from Morocco. World Development. 2017;91:28–52. doi: 10.1016/j.worlddev.2016.10.013

31. Burton G. An end to poverty in Brazil? An assessment of the Lula and Rousseff governments’ poverty reduction and elimination strategies. Journal of Policy Practice. 2013;12(3):194–215. doi: 10.1080/15588742.2013.796203

32. Elkins M. Embedding the vulnerable into the millennium development goals: social protection in poverty reduction strategy papers. Journal of International Development. 2014;26:853–874. doi: 10.1002/jid.2984

33. Vyas-Doorgapersad S. Gender equality in poverty reduction strategies for sustainable development: the case of South African local government. Journal of Social Development in Africa. 2014;29(2):105–134.

34. World Bank. World Development Report 1990: Poverty. Oxford University Press. New York, Washington, DC, USA. 1990.

35. Khan MS, Arefin TMS. Safety net, social protection, and sustainable poverty reduction: a review of the evidences and arguments for developing countries. IOSR Journal of Humanities and Social Science. 2013;15(2):23–29. ISSN (Online):2279–0837.

36. World Bank. Safety net programs and poverty reduction: lessons from cross-country experience. The World Bank, Washington, DC, USA. 1997.

37. Barrientos A, Hulme D, Shepherd A. Can social protection tackle chronic poverty? The European Journal of Development Research. 2005;17(1):8–23. doi: 10.1080/09578810500066456

38. Pradhan MAH, Mohammad S, Sulaiman J. An investigation of social safety net programs as means of poverty alleviation in Bangladesh. Asian Social Science. 2013;9(2):139–148. doi: 10.5539/ass.v9n2p139

39. Ahmed I, Jahan N, Fatema-Tuz-Zohora. Social safety net programme as a mean to alleviate poverty in Bangladesh. Developing Country Studies. 2014;4(17): 46–54. ISSN (Online):2225–0565.

40. Loison SA. Rural livelihood diversification in sub-Saharan Africa: a literature review. The Journal of Development Studies. 2015;51(9):1125–1138. doi: 10.1080/00220388.2015.1046445

41. Awotide DO, Kehinde A, Agbola P. Poverty and rural livelihood diversification among farming households in southwest Nigeria. Journal of Food, Agriculture, and Environment. 2010;8(1):367–371.

42. Martin SM, Lorenzen K. Livelihood diversification in rural Laos. World Development. 2016;83:231–243. doi: 10.1016/j.worlddev.2016.01.018

43. Oyinbo O, Olaleye KT. Farm households livelihood diversification and poverty alleviation in Giwa local government area of Kaduna State, Nigeria. Consilience: The Journal of Sustainable Development. 2016;15(1):219–232.

44. World Bank. Growing the rural non-farm economy to alleviate poverty: an evaluation of the contribution of the World Bank Group. The World Bank, Washington, DC, USA. 2017.

45. Stoian D, Donovan J, Fisk J, Muldoon MF. Value chain development for rural poverty reduction: a reality check and a warning. Enterprise Development and Micro-finance. 2012;23(1):54–69. doi: 10.3362/1755-1986.2012.006

46. Janda K, Rausser G, Strielkowski W. Determinants of profitability of polish rural micro-enterprises at the time of EU accession. Eastern European Countryside. 2013;19(1):177–193. doi: 10.2478/eec-2013-0009

47. Paoloni P, Dumay J. The relational capital of micro-enterprises run by women: the startup phase. VINE Journal of Information and Knowledge Management Systems. 2015;45(2):172–197. doi: 10.1108/VINE-01-2014-0003

48. Norell D, Janoch E, Kaganzi E, Tolat M, Lynn ML, Riley EC. Value chain development with the extremely poor: evidence and lessons from CARE, Save the Children, and World Vision. Enterprise Development and Micro-finance. 2017;28(1–2):44–62. doi: 10.3362/1755-1986.16–00024

49. Grindle MS. Good enough governance: poverty reduction and reform in developing countries. Governance. 2004;17(4):525–48.

50. Kwon H, Kim E. Poverty reduction and good governance: examining the rationale of the millennium development goals. Development and Change. 2014;45(2):353–375. doi: 10.1111/dech.12084

51. Davis TJ. Good governance as a foundation for sustainable human development in sub-Saharan Africa. Third World Quarterly. 2017;38(3):636–654. doi: 10.1080/01436597.2016.1191340

52. Khan MH. Governance, economic growth, and development. DESA Working Paper No.75. New York: UN Department of Economic and Social Affairs. 2009.

53. Earle L, Scott Z. Assessing the evidence of the impact of governance on development outcomes and poverty reduction. GSDRC Issues Paper. Birmingham: Governance and Social Development Resource Centre, University of Birmingham. 2010.

54. Cecchini S, Scott C. Can information and communications technology applications contribute to poverty reduction? Lessons from rural India. Information Technology for Development. 2003;10:73–84.

55. Heeks R. Do information and communication technologies (ICTs) contribute to development? Journal of International Development. 2010;22(5):625–640. doi: 10.1002/jid.1716/abstract

56. Sife AS, Kiondo E, Lyimo-Macha JG. Contribution of mobile phones to rural livelihoods and poverty reduction in Morogoro region, Tanzania. The Electronic Journal on Information Systems in Developing Countries. 2010;42(3):1–15.

57. Ika LA, Diallo A, Thuillier D. Critical success factors for World Bank projects: An empirical investigation. International Journal of Project Management. 2012;30:105–116. doi: 10.1016/j.ijproman.2011.03.005

58. Kosko B. Fuzzy cognitive maps. International Journal of Man-Machine Studies. 1986;24(1):65–75. doi: 10.1016/S0020-7373(86)80040-2

59. Gray SA, Gray S, De Kok JL, Helfgott AER, O'Dwyer B, Jordan R, et al. Using fuzzy cognitive mapping as a participatory approach to analyze change, preferred states, and perceived resilience of social-ecological systems. Ecology and Society. 2015;20(2):11. doi: 10.5751/ES-07396-200211

60. Özesmi U, Özesmi SL. Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach. Ecological Modeling. 2004;176(1–2):43–64. doi: 10.1016/j.ecolmodel.2003.10.027

61. Papageorgiou EI, Kontogianni A. Using fuzzy cognitive mapping in environmental decision making and management: a methodological primer and an application. International Perspectives on Global Environmental Change. 2012. Ch. 21.

62. Singh PK, Chudasama H. Pathways for drought resilient livelihoods based on people’s perception. Climatic Change. 2017a;140:179–193. doi: 10.1007/s10584-016-1817-8

63. Singh PK, Chudasama H. Assessing impacts and community preparedness to cyclones: a fuzzy cognitive mapping approach. Climatic Change. 2017b;143:337–354. doi: 10.1007/s10584-017-2007-z

64. Ziv G, Watson E, Young D, Howard DC, Larcom ST, Tanentzap AJ. The potential impact of Brexit on the energy, water and food nexus in the UK: a fuzzy cognitive mapping approach. Applied Energy. 2018;210:487–498. doi: 10.1016/j.apenergy.2017.08.033

65. Solana-Gutiérrez J, Rincón G, Alonso C, García-de-Jalón D. Using fuzzy cognitive maps for predicting river management responses: A case study of the Esla River basin, Spain. Ecological Modelling. 2017;360:260–269. doi: 10.1016/j.ecolmodel.2017.07.010

66. Singh PK, Nair A. Livelihood vulnerability assessment to climatic variability and change using fuzzy cognitive mapping approach. Climatic Change. 2014;127:475–491. doi: 10.1007/s10584-014-1275-0

67. Diniz FH, Kok K, Hoogstra-Klein M, Arts B. Mapping future changes in livelihood security and environmental sustainability based on perceptions of small farmers in the Brazilian Amazon. Ecology and Society. 2015;20(2):26. doi: 10.5751/ES-07286-200226

68. van der Sluis T, Arts B, Kok K, Bogers M, Busck AG, Sepp K, et al. Drivers of European landscape change: stakeholders’ perspectives through fuzzy cognitive mapping. Landscape Research. 2018;43:1–19. doi: 10.1080/01426397.2018.1446074

69. Falcone PM, Lopolito A, Sica E. Policy mixes towards sustainability transition in the Italian biofuel sector: Dealing with alternative crisis scenarios. Energy Research & Social Science. 2017;33:105–114. doi: 10.1016/j.erss.2017.09.007

70. Nápoles G, Papageorgiou EI, Bello R, Vanhoof K. On the convergence of sigmoid fuzzy cognitive maps. Information Sciences. 2016;349:154–171. doi: 10.1016/j.ins.2016.02.040

71. Kosko B. Hidden patterns in combined and adaptive knowledge networks. International Journal of Approximate Reasoning. 1988;2:377–393.

72. Jetter AJ, Kok K. Fuzzy cognitive maps for futures studies—a methodological assessment of concepts and methods. Futures. 2014;61:45–57. doi: 10.1016/j.futures.2014.05.002

73. van Vliet M, Kok K, Veldkamp T. Linking stakeholders and modellers in scenario studies: the use of fuzzy cognitive maps as a communication and learning tool. Futures. 2009;42:1–14. doi: 10.1016/j.futures.2009.08.005

74. Falcone PM, Lopolito A, Sica E. The networking dynamics of the Italian biofuel industry in time of crisis: Finding an effective instrument mix for fostering a sustainable energy transition. Energy Policy. 2018;112:334–348. doi: 10.1016/j.enpol.2017.10.036

75. Olazabal M, Pascual U. Use of fuzzy cognitive maps to study urban resilienceand transformation. Environmental Innovation and Societal Transitions. 2016;18:18–40. doi: 10.1016/j.eist.2015.06.006

76. Kok K. The potential of fuzzy cognitive maps for semi-quantitative scenario development, with an example from Brazil. Global Environmental Change. 2009;19:122–133. doi: 10.1016/j.gloenvcha.2008.08.003

77. Kim HS, Lee KC. Fuzzy implications of fuzzy cognitive map with emphasis on fuzzy causal relationship and fuzzy partially causal relationship. Fuzzy Sets and Systems. 1998;97(3):303–313. doi: 10.1016/S0165-0114(96)00349-1

78. Schneider M, Shnaider E, Kandel A, Chew G. Automatic construction of FCMs. Fuzzy Sets and Systems. 1998;93:161–172. doi: 10.1016/S0165-0114(96)00218-7

79. Vanwindekens FM, Stilmant D, Baret PV. Development of a broadened cognitive mapping approach for analysing systems of practices in social–ecological systems. Ecological Modelling. 2013;250:352–362. doi: 10.1016/j.ecolmodel.2012.11.023

80. Singh PK. Papageorgiou K, Chudasama H, Papageorgiou EI. Evaluating the Eectiveness of Climate Change Adaptations in the World’s Largest Mangrove Ecosystem. 2019;11(23): 6655. doi: 10.3390/su11236655

81. Falcone PM, Lopolito A, Sica E. Instrument mix for energy transition: A method for policy formulation. Technological Forecasting & Social Change. 2019:148: 119706. doi: 10.1016/j.techfore.2019.07.012

82. Morone P, Falcone PM, Lopolito A. How to promote a new and sustainable food consumption model: A fuzzy cognitive map study. Journal of Cleaner Production. 2019;208:563–574. doi: 10.1016/j.jclepro.2018.10.075

83. van Vliet M, Flörke M, Varela-Ortega C, Çakmak HE, Khadra R, Esteve P, et al. FCMs as a common base for linking participatory products and models. In: Gray S, Paolisso M, Jordan R, Gray S, editors. Environmental Modeling with Stakeholders, Theory, Methods, and Applications. 2017. pp. 145–170 (chapter 8).

84. Kosko B. Adaptive bidirectional associative memories. Applied Optics. 1987;26(23):4947–4960. doi: 10.1364/AO.26.004947 20523473

85. Kosko B. Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence/book and disk. Prentice Hall, Upper Saddle River. 1992a.

86. Kosko B. Neural networks for signal processing. Prentice Hall, Inc. 1992b.

87. Kyriakarakos G, Patlitzianas K, Damasiotis M, Papastefanakis D. A fuzzy cognitive maps decision support system for renewables local planning. Renewable and Sustainable Energy Reviews. 2014;39:209–222. doi: 10.1016/j.rser.2014.07.009

88. Jetter AJ, Schweinfort W. Building scenarios with fuzzy cognitive maps: an exploratory study of solar energy. Futures. 2011;43(1):52–66. doi: 10.1016/j.futures.2010.05.002

89. Amer M, Daim T, Jetter A. A review of scenario planning. Futures. 2013;46:23–40. doi: 10.1016/j.futures.2012.10.003

90. Mourhir A, Papageorgiou EI, Kokkinos K, Rachidi T. Exploring precision farming scenarios using fuzzy cognitive maps. Sustainability. 2017;9:1–23. doi: 10.3390/su9071241

91. Carvalho JP. On the semantics and the use of fuzzy cognitive maps and dynamic cognitive maps in social sciences. Fuzzy Sets and Systems. 2013;214:6–19. doi: 10.1016/j.fss.2011.12.009

92. Stylios CD, Groumpos PP. Fuzzy cognitive maps in modeling supervisory control systems. Journal of Intelligent and Fuzzy Systems. 2000;8:83–98. ISSN (Online):1064–1246.

93. Papageorgiou EI, Stylios CD, Groumpos PP. Active Hebbian learning algorithm to train fuzzy cognitive maps. International Journal of Approximate Reasoning. 2004;37:219–249. doi: 10.1016/j.ijar.2004.01.001

94. Stylios CD, Georgopoulos VC, Groumpos PP, editors. The use of fuzzy cognitive maps in modeling systems. In: Proceedings of 5th IEEE Mediterranean conference on control and systems; 1997; Paphos, Cyprus; pp 21–23. 1997.

95. Pedrycz W. The design of cognitive maps: a study in synergy of granular computing and evolutionary optimization. Expert Systems with Applications. 2010;37(10):7288–7294. doi: 10.1016/j.eswa.2010.03.006

96. Amer M, Daim TU, Jetter A. Technology roadmap through fuzzy cognitive map-based scenarios: the case of wind energy sector of a developing country. Technology Analysis & Strategic Management. 2016;28:131–55. doi: 10.1080/09537325.2015.1073250

97. Allen M, Dube OP, Solecki W, Aragón–Durand F, Cramer W, Humphreys S, et al. Framing and Context. In: Masson-Delmotte V, Zhai P, Pörtner HO, Roberts D, Skea J, Shukla PR, et al. editors. Global warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. 2018. In Press.


Článek vyšel v časopise

PLOS One


2020 Číslo 1
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Svět praktické medicíny 1/2024 (znalostní test z časopisu)
nový kurz

Koncepce osteologické péče pro gynekology a praktické lékaře
Autoři: MUDr. František Šenk

Sekvenční léčba schizofrenie
Autoři: MUDr. Jana Hořínková

Hypertenze a hypercholesterolémie – synergický efekt léčby
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Význam metforminu pro „udržitelnou“ terapii diabetu
Autoři: prof. MUDr. Milan Kvapil, CSc., MBA

Všechny kurzy
Kurzy Podcasty Doporučená témata Časopisy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#