Have a personal or library account? Click to login
Predictor of willingness to pay for early warning climate system and agronomy advisories services in Albania: A case study of medicinal plant in “Malesi e Madhe” Cover

Predictor of willingness to pay for early warning climate system and agronomy advisories services in Albania: A case study of medicinal plant in “Malesi e Madhe”

By: Irida Gjermeni  
Open Access
|Sep 2024

References

  1. Afuye, G. A., Kalumba, A. M., and Orimoloye, I. R. (2021b). Characterisation of vegetation response to climate change: a review. Sustainability 13:7265. doi: 10.3390/su13137265
  2. Afuye, G. A., Kalumba, A. M., Busayo, E. T., and Orimoloye, I. R. (2021a). A bibliometric review of vegetation response to climate change. Environ. Sci. Poll. Res. 7, 113. doi: 10.1007/s11356-021-163197
  3. Akadiri, O. P. (2011). Development of a multi-criteria approach for the selection of sustainable materials for building projects. PhD Thesis - University of Wolverhampton, 1–437.
  4. Akhmedova, A., Marimon, F. and Mas-Machuca, M. (2020), “Winning strategies for customer loyalty in the sharing economy: a mixed-methods study”, Journal of Business Research, Vol. 112, pp. 33-44.
  5. Akhtar, S., Wajeeha, S., Wania M N., Isra, Sh., Ayeza, I.. (2016). “Assessment of Willingness to Pay for Improved Air Quality using Contingent Valuation Method.” Global Journal of Environmental Science and Management, 3(3): 279–286.
  6. Antwi-Agyei, P., Amanor, K., Hogarh, J.N., Dougill, A.J., (2021a). Predictors of access to and willingness to pay for climate information services in north-eastern Ghana: a gendered perspective. Environ. Develop. 37, 100580 https://doi.org/10.1016/j.envdev.2020.100580.
  7. Antwi-Agyei, P., Dougill, A.J., Abaidoo, R.C., (2021b). Opportunities and barriers for using climate information for building resilient agricultural systems in Sudan savannah agroecological zone of north-eastern Ghana. Clim. Serv. 22, 100226 https://doi.org/10.1016/j.cliser.2021.100226.
  8. Antwi-Agyei, P., Stringer, L.C., (2021). Improving the effectiveness of agricultural extension services in supporting farmers to adapt to climate change: Insights from northeastern Ghana. Clim. Risk Manag. 32, 100304 https://doi.org/10.1016/j.crm.2021.100304
  9. Brida, A. B., Owiyo, T. and Sokona, Y. (2013). Loss and Damage from the Double Blow of Flood and Drought in Mozambique. Int. J. Glob.Warm., 5(4): 514-531.
  10. Chung, Ill & Kim, Jong & Lim, Jung & Yu, Chang & Kim, Seung & Hahn, Sang. (2006). Comparison of resveratrol, SOD activity, phenolic compounds and free amino acids in Rehmannia glutinosa under temperature and water stress. Environmental and Experimental Botany. 56. 44-53. 10.1016/j.envexpbot.2005.01.001.
  11. Costello, A.B. and Osborne, J.W. (2005), “Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis”, Practical Assessment, Research, and Evaluation, Vol. 10 No. 1, p. 7.
  12. Darnhofer, I. (2014) Resilience and why it matters for farm management. Eur. Rev. Agric. Econ., 41, 461–484.
  13. de Winter, J.C., Dodou, D. and Wieringa, P.A. (2009), “Exploratory factor analysis with small sample sizes”, Multivariate Behavioral Research, Vol. 44 No. 2, pp. 147-181.
  14. Dinku, T., Block, P., Sharoff, J., Hailemariam, K., Osgood, D., del Corral, J., Thomson, M. (2014). Bridging critical gaps in climate services and applications in Africa. Earth Perspectives, 1(15): 1-13.
  15. Ebi, L., Loladze, I., (2019) Elevated atmospheric CO2 concentrations and climate change will affect our food’s quality and quantity
  16. Enenkel, M., See, L., Bonifacio, R., Boken, V., Chaney, N., Vinck, P., et al. (2015). Drought and food security–Improving decision-support via new technologies and innovative collaboration. Glob. Food Security 4, 51–55. doi: 10.1016/j.gfs.2014.08.005
  17. Falco, C., Galeotti, M. and Olper, A. (2019). Climate Change and Migration: Is[ Downloaded from jast.modares.ac.ir on 2024-07-24 Agriculture the Main Channel?. Glob.Environ. Change, 59: 101995
  18. Fay Buckland, S., & Campbell, D. (2021). An Assessment of Factors Influencing Awareness, Access and Use of Agro-Climate Services among Farmers in Clarendon, Jamaica. Geoforum, 126, 171-191.https://doi.org/10.1016/j.geoforum.2021.07.032
  19. Huong, N. T. L., Bo, Y. S. and Fahad, S.(2019). Economic Impact of Climate Change on Agriculture Using Ricardian Approach: ACase of Northwest Vietnam. J. Saudi Soc. Agric. Sci., 18(4): 449-457.
  20. Jochum GM, Mudge KW, Thomas RB. (2007) Elevated temperatures increase leaf senescence and root secondary metabolite concentrations in the understory herb Panax quinquefolius (Araliaceae). Am J Bot. May;94(5):819-26. doi: 10.3732/ajb.94.5.819. PMID: 21636451.
  21. Kaiser, H.F. (1974), “An index of factorial simplicity”, Psychometrika, Vol. 39 No. 1, pp. 31-36.
  22. Khan I., Lei H., Shah I.A., Ali I., Khan I., Muhammad I., Huo X., Javed T.(2020) Farm households’ risk perception, attitude and adaptation strategies in dealing with climate change: Promise and perils from rural Pakistan. Land Use Policy. 91:104395. doi: 10.1016/j.landusepol.2019.104395.
  23. Kim, I., Ikpe, E., Sawa, B., (2016). Analysing the Importance of Climate Forecast Information for Transhumance Pastoralists in Katsina State, Nigeria. Joint International Conference. https://doi.org/10.1080/17565529.2015.1034231.
  24. Kumari, A.; Lakshmi, G.A.; Krishna, G.K.; Patni, B.; Prakash, S.; Bhattacharyya, M.; Singh, S.K.; Verma, K.K. ( 2022) Climate Change and Its Impact on Crops: A Comprehensive Investigation for Sustainable Agriculture. Agronomy , 12, 3008. https://doi.org/10.3390/agronomy12123008
  25. Ling, X., (2022), Effect of Farmers’ Awareness of Climate Change on Their Willingness to Adopt Low-Carbon Production: Based on the TAM-SOR Model, doi: 10.3390/ijerph20010619
  26. Loboguerrero, A. M., Campbell, B. M.,Cooper, P. J. M., Hansen, J., Rosenstock, T.and Wollenberg, E. (2019). Food and Earth Systems: Priorities for Climate Change Adaptation and Mitigation for Agriculture and Food Systems. Sustainability, 11: 1-2
  27. Mase, A., & Prokopy, L. (2014). Unrealized potential: A review of perceptions and use of weather and climate information in agricultural decision making. Weather, Climate, and Society, 6: 47-61
  28. Muema, E., Mburu, J., Coulibaly, J., Mutune, J., (2018). Determinants of access and utilisation of seasonal climate information services among smallholder farmers in
  29. Mulliri, J., Shahu, E., Baraku, B., (2021). Information systems in albanian agriculture; problems and future challenges. Conferencii. 1. 10.51586/BMESS2021-5.
  30. Mysiak, Jaroslav & De Salvo, Maria & Santato, Silvia & Amadio, Mattia. (2013). Economic Impacts of Drought on Agriculture. SSRN Electronic Journal. 10.2139/ssrn.2637399.
  31. Ogisi, O.D. and Begho, T. (2023) Sub-Saharan Africa Africa Adoption of climate smart agriculture
  32. Ogisi, O.D., Begho, T., (2023). Adoption of climate-smart agricultural practices in sub-Saharan Africa: a review of the progress, barriers, gender differences and recommendations. Farming Syst. 1, 100019 https://doi.org/10.1016/j.farsys.2023.100019.
  33. Olya, H.G. and Altinay, L. (2016), “Asymmetric modeling of intention to purchase tourism weather insurance and loyalty”, Journal of Business Research, Vol. 69 No. 8, pp. 2791-2800.
  34. Onyeneke, C.J., Umeh, G.N., Onyeneke, R.U., (2023). Impact of climate information services on crop yield in Ebonyi State, Nigeria. Climate 11, 7. https://doi.org/10.3390/cli11010007
  35. Onyeneke, Chinenye & Umeh, Gibson & Onyeneke, Robert. (2022). Impact of Climate Information Services on Crop Yield in Ebonyi State, Nigeria. Climate. 11. 7. 10.3390/cli11010007.
  36. Orimoloye, I., (2022), Agricultural Drought and Its Potential Impacts: Enabling Decision-Support for Food Security in Vulnerable Regions, https://doi.org/10.3389/fsufs.2022.838824
  37. Oyekale, A.S., (2015). Access to risk mitigating weather forecasts and changes in farming operations in east and west Africa: evidence from a baseline survey. Sustainability 7,14599–14617. https://doi.org/10.3390/su71114599
  38. Pant P, Pandey S, Dall’Acqua S.(2021) The influence of environmental conditions on secondary metabolites in medicinal plants: A literature review. Chemistry and Biodiversity.;18(11). doi:10.1002/cbdv.202100345
  39. Perera, D.; Agnihotri, J.; Seidou, O.; Djalante, R. (2020) Identifying societal challenges in flood early warning systems. Int. J. Disaster Risk Reduct, 51, 101794.
  40. Roy S, Roy D, (2016), Use of Medicinal Plant and Its Vulnerability Due to Climate Change in Northern Part of Bangladesh, American Journal of Plant Sciences, Vol.7 No.13, 2016
  41. Thomalla, F.; Larsen, R.K.(2010) Resilience in the context of tsunami early warning systems and community disaster preparedness in the Indian Ocean region. Environ. Hazards, 9, 249–265.
  42. Velicer, W.F. and Fava, J.L. (1998), “Effects of variable and subject sampling on factor pattern recovery”, Psychological Methods, Vol. 3, pp. 231-251.
  43. Weide, A.C. and Beauducel, A. (2019), “Varimax rotation based on gradient projection is a feasible alternative to SPSS”, Frontiers in Psychology, Vol. 10.
  44. Wens M.L., Mwangi M.N., van Loon A.F., Aerts J.C.(2021) Complexities of drought adaptive behaviour: Linking theory to data on smallholder farmer adaptation decisions. Int. J. Disaster Risk Reduct. 63:102435. doi: 10.1016/j.ijdrr.2021.102435.
  45. Yaseen, Z. M., and Shahid, S. (2021). Drought index prediction using data intelligent analytic models: a review. Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation 2021, 127. doi: 10.1007/978-981-15-5772-9_1
DOI: https://doi.org/10.2478/bjir-2024-0017 | Journal eISSN: 2411-9725 | Journal ISSN: 2410-759X
Language: English
Page range: 64 - 79
Published on: Sep 14, 2024
In partnership with: Paradigm Publishing Services
Publication frequency: 3 issues per year

© 2024 Irida Gjermeni, published by International Institute for Private, Commercial and Competition Law
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.