Aquaculture Farmers’ Spatial Distribution and Intention to Adopt the Sistem Pengurusan Kawalan Biosekuriti Perikanan (Biodof-Map)

Eleanor Daniella Lokman, Norsida Man and Che Ya Nik Norasma
Additional contact information
Eleanor Daniella Lokman: Department of Agribusiness and Bioresource Economics, Faculty of Agriculture, Universiti Putra Malaysia (UPM), Selangor, 43400 UPM, Serdang
Norsida Man: Fisheries Research Institute (FRI) Batu Maung, 11960, Pulau Pinang, Malaysia
Che Ya Nik Norasma: Department of Agribusiness and Bioresource Economics, Faculty of Agriculture, Universiti Putra Malaysia (UPM), Selangor, 43400 UPM, Serdang Department of Agriculture Technology, Faculty of Agriculture, Universiti Putra Malaysia (UPM), 43400, Serdang, Malaysia

International Journal of Research and Innovation in Social Science, 2024, vol. 8, issue 7, 695-704

Abstract: Aquaculture is crucial to food supply and economic growth supported by Industry Revolution 4.0 to boost output. Malaysian Department of Fisheries (DOF) developed a Web-GIS system, a spatial system focusing on aquaculture. However, farmers are unfamiliar with the system. The Theory of Planned Behaviour (TPB) is employed to examine the attitudes, subjective norms, and perceived behavioural control of Malaysian Aquaculture Farmers (MAFs) throughout Malaysia in relation to BioDOF-Map. Questionnaire was used in the present quantitative research, with 278 respondents. Data was analysed using descriptive, spatial, correlation, and regression analysis techniques. 65.8% of respondents are farm landlords. 29.2% respondents own 3.1 to 4 hectares, and 69.1% reside 2 to 3 km from their farm. Notably, 49.6% own family land and 9.7% grow crops or vegetables off-farm. Cage culture or aquaculture were respondents’ activities. Perak (11.15%), Pahang and Selangor (10.07%) have the most residents. Spatially, aquaculture farming decisions are influenced by housing and town location. With a mean of 4.55 and SD of 0.296, MAFs intend to use BioDOF-Map. Correlation showed a significant association between attitude and intention at 0.01 level of significance (r=0.980, p=.000), supporting the hypothesis. At 0.01 significance level, subjective norms, and intention are linear (r = 0.325, p =.000), fails to reject the null hypothesis. At 0.01 level of significance (r=0.966, p=.000), perceived behavioural control and intention fails to reject the null hypothesis. Regression shows a significant association between attitude and intention (β = 0.635, t = 20.704, p

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.rsisinternational.org/journals/ijriss/ ... -issue-7/695-704.pdf (application/pdf)
https://rsisinternational.org/journals/ijriss/arti ... erikanan-biodof-map/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bcp:journl:v:8:y:2024:i:7:p:695-704

Access Statistics for this article

International Journal of Research and Innovation in Social Science is currently edited by Dr. Nidhi Malhan

More articles in International Journal of Research and Innovation in Social Science from International Journal of Research and Innovation in Social Science (IJRISS)
Bibliographic data for series maintained by Dr. Pawan Verma ().