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Local participation in community forest management using theory of planned behaviour: evidence from Udon Thani Province, Thailand

  • Chidchanok Apipoonyanon
  • Sylvia SzaboEmail author
  • John K. M. Kuwornu
  • Mokbul Morshed Ahmad
Original Article
  • 9 Downloads

Abstract

Effective participatory management of natural resources is critical for long-term environmental sustainability and the well-being of the local population. This study used the theory of planned behaviour to examine participation in community forest management. Primary data were collected through household survey, and hypotheses were tested by using the structural equation modelling approach. The empirical results revealed that attitude, subjective norms, perceived behavioural control and self-efficacy are significant predictors of local participation. The results further showed that individuals aged 46–60 years, farmers and those earning at least 20,001 Thai Baht per month were more likely to have positive attitudes towards participation in community forest management programs. Therefore, the government should consider intensifying efforts to engage these groups in participatory policy-making.

Keywords

Community forest development Theory of planned behaviour Local participation Structural equation modelling Thailand 

Résumé

Une gestion participative efficace des ressources naturelles est essentielle à la pérennité environnementale et au bien-être des populations locales sur le long terme. Cette étude a utilisé la théorie du comportement planifié pour examiner la participation à la gestion communautaire des forêts. Des données primaires ont été collectées par le biais d’une enquête auprès des ménages et les hypothèses ont été testées en utilisant l’approche de modélisation par équation structurelle. Les résultats empiriques ont révélé que l’attitude, les normes subjectives, le contrôle comportemental perçu et l’efficacité personnelle sont les prédicteurs les plus significatifs de la participation locale. Les résultats ont également montré que les individus âgés de 46 à 60 ans, les agriculteurs et ceux gagnant au moins 20 001 Baht thaïlandais par mois étaient plus susceptibles d’avoir une attitude positive à l’égard de la participation aux programmes de gestion communautaire des forêts. Par conséquent, le gouvernement devrait envisager d’intensifier ses efforts pour faire participer ces groupes à l’élaboration de politiques participatives.

Notes

Acknowledgements

This research would not have been possible without the full cooperation of many individuals. The authors would like to express their gratitude to the Director of Community Forest Management Bureau, Royal Forest Department and the staff at Udon Thani Provincial Department of Royal Forest Office for their valuable help, opinions and information with regard to this research project. We also thank Mrs. Lumpai and Mr. Noi, the community forest committee and the villagers from Huai Rai Burapa and Nong Bua Ngern villages for providing their expertise and access to facilities for the purposes of this research.

References

  1. Aimran, A., and S. Ahmad. 2013. Assessing the unidimensionality, reliability, validity and fitness of influential factors of 8th grades student’s mathematics achievement in Malaysia. International Journal of Advanced Research 1 (2): 1–5.Google Scholar
  2. Ajzen, I. 1985. From intentions to actions: A theory of planned behavior. In Action control: From cognition to behavior, ed. J. Kuhl and J. Beckmann, 11–39. Berlin: Springer.  https://doi.org/10.1007/978-3-642-69746-3_2.CrossRefGoogle Scholar
  3. Ajzen, I. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Process 50 (2): 179–211.  https://doi.org/10.1016/0749-5978(91)90020-T.CrossRefGoogle Scholar
  4. Ajzen, I. (2002), Constructing a TPB questionnaire: Conceptual and methodological considerations [WWW Document]. URL http://www-nix.oit.umass.edu/~aizen/tpb.html.
  5. Ajzen, I., and M. Fishbein. 1977. Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin 84 (5): 888–918.  https://doi.org/10.1037/0033-2909.84.5.888.CrossRefGoogle Scholar
  6. Ajzen, I., and M. Fishbein. 1988. Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice Hall Print.Google Scholar
  7. Bamberg, S., and P. Schmidt. 2003. Incentives, morality, or habit? Predicting students’ car use for university routes with the models of Ajzen, Schwartz, and Triandis. Environment Behavior 35 (2): 264–285.  https://doi.org/10.1177/0013916502250134.CrossRefGoogle Scholar
  8. Bagozzi, R.P., and Y. Yi. 1988. On the evaluation of structural equation models. Journal of the Academy of Marketing Sciences 16 (1): 74–94.  https://doi.org/10.1007/BF02723327.CrossRefGoogle Scholar
  9. Bandura, A. 1978. Self-efficacy: Toward a unifying theory of behavioral change. Advance in Behavior Research and Therapy 1 (4): 139–161.  https://doi.org/10.1016/0146-6402(78)90002-4.CrossRefGoogle Scholar
  10. Bennett, N.J. 2016. Using perceptions as evidence to improve conservation and environmental management. Conservation Biology 30 (3): 582–592.  https://doi.org/10.1111/cobi.12681.CrossRefGoogle Scholar
  11. Bhatia, S., S.M. Redpath, K. Suryawanshi, and C. Mishra. 2017. The relationship between religion and attitudes toward large carnivores in Northern India? Human Dimensions of Wildlife 22 (1): 30–42.  https://doi.org/10.1080/10871209.2016.1220034.CrossRefGoogle Scholar
  12. Black, R., and P.B. Cobbinah. 2018. Local attitudes towards tourism and conservation in rural Botswana and Rwanda. Journal of Ecotourism 17 (1): 79–105.  https://doi.org/10.1080/14724049.2016.1258074.CrossRefGoogle Scholar
  13. Bollen, K.A., and S. Bauldry. 2011. Three Cs in measurement models: Causal indicators, composite indicators, and covariates. Psychology Methods 16 (3): 265–284.  https://doi.org/10.1037/a0024448.Three.CrossRefGoogle Scholar
  14. Bollen, K.A., and W.R. Davis. 2009. Two rules of identification for structural equation models. Structural Equation Modeling: A Multidisciplinary Journal 16 (3): 523–536.  https://doi.org/10.1080/10705510903008261.CrossRefGoogle Scholar
  15. Castilho, L.C., K.M. De Vleeschouwer, E.J. Milner-Gulland, and A. Schiavetti. 2018. Attitudes and behaviors of rural residents toward different motivations for hunting and deforestation in protected areas of the northeastern Atlantic forest, Brazil. Tropical Conservation Science 11: 1940082917753507.  https://doi.org/10.1177/1940082917753507.CrossRefGoogle Scholar
  16. Fischer, A.P. 2018. Pathways of adaptation to external stressors in coastal natural-resource-dependent communities: Implications for climate change. World Development 108: 235–248.  https://doi.org/10.1016/j.worlddev.2017.12.007.CrossRefGoogle Scholar
  17. Fishbein, M., and I. Ajzen. 2010. Predicting and changing behavior: The reasoned action approach. New York: Psychology Press, Taylor and Francis Group.Google Scholar
  18. Giles, M., C. McClenahan, E. Cairns, and J. Mallet. 2004. An application of the theory of planned behaviour to blood donation: The importance of self-efficacy. Health Education Research 19 (4): 380–391.  https://doi.org/10.1093/her/cyg063.CrossRefGoogle Scholar
  19. Gruver, J.B., A.L. Metcalf, A.B. Muth, J.C. Finley, and A.E. Luloff. 2017. Making decisions about forestland succession: Perspectives from Pennsylvania’s private forest landowners. Society and Natural Resources 30 (1): 47–62.  https://doi.org/10.1080/08941920.2016.1180728.CrossRefGoogle Scholar
  20. Hair, J.F., W.C. Black, B.J. Babin, and R.E. Anderson. 2010. Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice Hall.Google Scholar
  21. Hickerson, S.C., M.L. Fleming, R.V. Sawant, N.D. Ordonez, and S.S. Sansgiry. 2017. Predicting pharmacy students’ intention to apply for a residency: A systematic theory of planned behavior approach. Currents in Pharmacy Teaching and Learning 9 (1): 12–19.  https://doi.org/10.1016/j.cptl.2016.08.047.CrossRefGoogle Scholar
  22. Hong, K., J. Gittelsohn, and H. Joung. 2010. Determinants of customers’ intention to participate in a Korean restaurant health promotion program: An application of the theory of planned behavior. Health Promotion International 25 (2): 174–182.  https://doi.org/10.1093/heapro/daq005.CrossRefGoogle Scholar
  23. Kaplan-Hallam, M., and N.J. Bennett. 2018. Adaptive social impact management for conservation and environmental management. Conservation Biology 32 (2): 304–314.  https://doi.org/10.1111/cobi.12985.CrossRefGoogle Scholar
  24. Karppinen, H., and S. Berghäll. 2015. Forest owners’ stand improvement decisions: Applying the theory of planned behavior. Forest Policy and Economics 50: 275–284.  https://doi.org/10.1016/j.forpol.2014.09.009.CrossRefGoogle Scholar
  25. Kil, N., S.M. Holland, and T.V. Stein. 2014. Structural relationships between environmental attitudes, recreation motivations, and environmentally responsible behaviors. Journal of Outdoor Recreation and Tourism 7–8: 16–25.  https://doi.org/10.1016/j.jort.2014.09.010.CrossRefGoogle Scholar
  26. Laakkonen, A., R. Zimmerer, T. Kähkönen, T. Hujala, T. Takala, and J. Tikkanen. 2018. Forest owners’ attitudes toward pro-climate and climate-responsive forest management. Forest Policy and Economics 87: 1–10.  https://doi.org/10.1016/j.forpol.2017.11.001.CrossRefGoogle Scholar
  27. Li, Y., and C. Zhong. 2017. Factors driving consumption behavior for green aquatic products: Empirical research from Ningbo, China. British Food Journal 119 (7): 4–22.  https://doi.org/10.1108/BFJ-10-2016-0456.CrossRefGoogle Scholar
  28. Lin, L.P.L., C.Y. Yu, and F.C. Chang. 2018. Determinants of CSER practices for reducing greenhouse gas emissions: From the perspectives of administrative managers in tour operators. Tourism Management 64: 1–12.  https://doi.org/10.1016/j.tourman.2017.07.013.CrossRefGoogle Scholar
  29. Maat, S.M., E. Zakaria, N.N.M. Nordin, and T.S.M. Meerah. 2011. Confirmatory factor analysis of the mathematics teachers’ teaching practices instrument. World Applied Sciences Journal 12 (11): 2092–2096.Google Scholar
  30. Mbaiwa, J.E. 2018. Effects of the safari hunting tourism ban on rural livelihoods and wildlife conservation in Northern Botswana. South African Geographical Journal 100 (1): 41–61.  https://doi.org/10.1080/03736245.2017.1299639.CrossRefGoogle Scholar
  31. Ministry of Foreign Affairs. 2017. Thailand’s voluntary national review on the implementation of the 2030 agenda for sustainable development. Bangkok: Department of International Organizations, Ministry of Foreign Affairs of Thailand.Google Scholar
  32. Mueller, J.T., B.D. Taff, J. Wimpey, and A. Graefe. 2018. Small-scale race events in natural areas: Participants’ attitudes, beliefs, and global perceptions of leave no trace ethics. Journal of Outdoor Recreation and Tourism 23: 8–15.  https://doi.org/10.1016/j.jort.2018.03.001.CrossRefGoogle Scholar
  33. Pramudwinai, D. 2018. Thailand’s voluntary national review on the implementation of the 2030 agenda for sustainable development. Bangkok, Thailand.Google Scholar
  34. Rhodes, T.K., F.X. Aguilar, S. Jose, and M. Gold. 2018. Factors influencing the adoption of riparian forest buffers in the Tuttle Creek Reservoir watershed of Kansas, USA. Agroforestry Systems 92 (3): 739–757.  https://doi.org/10.1007/s10457-016-0045-6.CrossRefGoogle Scholar
  35. Sun, Y., S. Wang, J. Li, D. Zhao, and J. Fan. 2017. Understanding consumers’ intention to use plastic bags: Using an extended theory of planned behaviour model. National Hazards 89 (3): 1327–1342.  https://doi.org/10.1007/s11069-017-3022-0.CrossRefGoogle Scholar
  36. Szabo, S. 2016. Urbanisation and food insecurity risks: Assessing the role of human development. Oxford Development Studies 44 (1): 28–48.  https://doi.org/10.1080/13600818.2015.1067292.CrossRefGoogle Scholar
  37. Tabachnick, B.G., and L.S. Fidell. 2013. Using multivariate statistics, 6th ed. Boston, MA: Allyn & Bacon/Pearson.Google Scholar
  38. Tesfaye, Y., A. Roos, and F. Bohlin. 2012. Attitudes of local people towards collective action for forest management: The case of participatory forest management in Dodola area in the Bale Mountains, Southern Ethiopia. Biodiversity and Conservation 21 (1): 245–265.  https://doi.org/10.1007/s10531-011-0181-2.CrossRefGoogle Scholar
  39. Tobbin, P., and J.K.M. Kuwornu. 2011. Adoption of mobile money transfer technology: Structural equation modeling approach. European Journal of Business and Management 3 (7): 59–77.Google Scholar
  40. Wu, S.T., and Y.S. Chen. 2018. Local intentions to participate in ecotourism development in Taiwan’s Atayal communities. Journal of Tourism and Cultural Change 16 (1): 75–96.  https://doi.org/10.1080/14766825.2016.1253705.CrossRefGoogle Scholar
  41. Zainudin, A., A. Asyraf, and M. Mustafa. 2016. The Likert scale analysis using parametric based structural equation modeling (SEM). Computational Methods in Social Sciences 4 (1): 13–21.Google Scholar

Copyright information

© European Association of Development Research and Training Institutes (EADI) 2019

Authors and Affiliations

  • Chidchanok Apipoonyanon
    • 1
  • Sylvia Szabo
    • 1
    Email author
  • John K. M. Kuwornu
    • 2
  • Mokbul Morshed Ahmad
    • 1
  1. 1.Department of Development and Sustainability, School of Environment, Resources and DevelopmentAsian Institute of TechnologyKlong LuangThailand
  2. 2.Department of Food, Agriculture and Bioresources, School of Environment, Resources and DevelopmentAsian Institute of TechnologyKlong LuangThailand

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