Structural modelling of collective action behavior of farmers for natural resource management


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Authors

  • PRITI PRIYADARSHNI ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • R N PADARIA ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • R R BURMAN ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • RASHMI SINGH ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • SANJOY BANDYOPADHYAY ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • PRAMOD KUMAR ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • ARPAN BHOWMIK ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
  • ROMEN SHARMA ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India

https://doi.org/10.56093/ijas.v92i1.120847

Keywords:

Collective action, Natural resource management, Structural equation modelling

Abstract

Community engagement is a crucial element for effective management of natural resources. This study is aimed at determining the factors and analyzing their path for collective action behavior of farmers towards natural resource management. Two cases of community based natural resource management were conducted in Phek and Kohima districts of Nagaland during 2020 and with thematic their analysis of activities, the probable factors of collective action among the communities were listed. Through participatory rural appraisal, focus group discussion and personal interview method data, was collected with a total sample size of randomly selected 106 farmers. The composite reliability for the explanatory variables, viz. social cohesiveness, normative belief, collective action for resource management, trust, community orientation, social relationship, and shared values were 0.79, 0.81,0.92, 0.6, 0.72, 0.78, and 0.52, respectively. Exploratory factor analysis resulted in 7 factors with 63.7% of the total variance explained. The obtained factors were validated through measurement modelling by confirmatory factor analysis. The structural model had goodness of fit with acceptable values of RMSEA (0.09), GFI (0.96) and CFI (0.92). The relationship of community orientation was found highly significant with normative belief (Z=6.36**); social cohesiveness (2.27**) and collective action (Z=3.47**). Emphasis should be laid upon promotion of normative beliefs, local institutions, and social values for augmentation of collective action for natural resource management.

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References

A B Hamid M R, Sami W and Sidek M H M. 2017. Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. Journal of Physics: Conference Series 890(1):012163.

Armitage D. 2005. Adaptive capacity and community-based natural resource management. Environmental management 35(6): 703–15.

Bandura A. 1971. Social learning theory. General Learning Press. 79, Madison Avenue, New York City, USA.

Blackmore C, Ison R and Jiggins J. 2007. Social learning: an alternative policy instrument for managing in the context of Europe's water. Environmental Science and Policy 10(6): 493–98.

Fishbein M, Jaccard J, Davidson A R, Ajzen I and Loken B. 1980. Predicting and understanding family planning behaviors. Understanding Attitudes and Predicting Social Behavior. Prentice Hall, New Jesey, USA.

Fornell C and Larcker D F. 1981. Structural equation models with unobservable variables and measurement error: Algebra and Statistics. Journal of Marketing Research 18 (3): 382–88.

Forza C and Filippini R. 1998. TQM impact on quality conformance and customer satisfaction: a causal model. International journal of production economics 55(1): 1–20.

Hair J, Hult G T M, Ringle C and Sarstedt M. 2016. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publications, UK.

Häuberer J. (2010). Social Capital Theory. Research, Towards a methodological foundation. Springer, New York, USA.

Hu L T and Bentler P M. 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal 6(1): 1–55.

Irvine K N, O’Brien L, Ravenscroft N, Cooper N, Everard M, Fazey I, Marks S Reed and Kenter J O. 2016. Ecosystem services and the idea of shared values. Ecosystem Services 21: 184–93.

Jöreskog K G and Sörbom D.1984. LISREL VI: Analysis of linear structural relationships by maximum likelihood, instrumental variables, and least squares methods. Scientific Software.

Keen M, Brown, V A and Dyball R. 2005. Social Learning in Environmental Management: Towards a Sustainable Future. Routledge, UK.

Kline R B. 2011. Convergence of structural equation modeling and multilevel modeling. The Sage Handbook of Innovation in Social Research Methods, SAGE Publications, UK.

Lam T Y and Maguire D A. 2012. Structural equation modeling: theory and applications in forest management. International Journal of Forestry Research. 2012.doi:10.1155/2012/263953; https://www.hindawi.com/journals/ijfr/2012/263953/

Matthies A L, Kattilakoski M and Ran Tamaki N. 2011. Citizens' participation and community orientation–indicators of social sustainability of rural welfare services. Nordic Social Work Research 1(2): 125–39.

Möllering G. 2006. Trust, Institutions, Agency: Towards a Neoinstitutional Theory of Trust. Handbook of Trust Research. pp. 355-376.

Bachmann R, Zaheer A (Eds), Cheltenham: Edward Elgar, Pahl-Wostl C and Hare M. 2004. Processes of social learning in integrated resources management. Journal of Applied and Community Psychology 14: 193–206

Park S Y. 2009. An analysis of the technology acceptance model in understanding university students' behavioral intention to use e-learning. Journal of Educational Technology and Society 12(3): 150–62.

Portney L and Watkins M. 2000. Foundations of Clinical Research, Vol 2. Prentice-Hall, New Jersey.

Reber R and Norenzayan A. 2018. Shared fluency theory of social cohesiveness: How the metacognitive feeling of processing fluency contributes to group processes. Metacognitive Diversity: An interdisciplinary approach. pp. 47–67. J Proust, M. Fortier (Eds). Oxford University Press, UK.

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Submitted

2022-01-31

Published

2022-01-31

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How to Cite

PRIYADARSHNI, P., PADARIA, R. N., BURMAN, R. R., SINGH, R., BANDYOPADHYAY, S., KUMAR, P., BHOWMIK, A., & SHARMA, R. (2022). Structural modelling of collective action behavior of farmers for natural resource management. The Indian Journal of Agricultural Sciences, 92(1), 95-100. https://doi.org/10.56093/ijas.v92i1.120847
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