Evaluating beekeeping practices through structural equation modeling and artificial neural network analysis
Bibliographic Data
| ID | 22232013 |
|---|---|
| Authors | A Al Mamun (0000-0002-9713-742X, National University of Malaysia, corresponding author), Naeem Hayat (0000-0003-0756-5226, Sohar University), Qing Yang (0000-0001-6621-080X, National University of Malaysia), Muhammad Mehedi Masud (0000-0003-0476-4481, University of Malaya) |
| Year | 2025 |
| Volume | 12 |
| Issue | 1 |
| Publication date | 2025-11-28 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Humanities and Social Sciences Communications (JOURNAL) |
| Journal identifiers | ISSN: 2662-9992 • E-ISSN: 2662-9992 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1057/s41599-025-06144-5 |
| OpenAlex | W4416794656 |
| Language | EN |
| References cited | 36 |
This study examined the intention and behavior related to adopting beekeeping among low-income households using the theory of planned behavior. It employed a cross-sectional design, and quantitative data were collected via structured interviews with 420 low-income families residing in rural Peninsular Malaysia. The final analysis was performed using partial least squares structural equation modeling and artificial neural network analysis. The findings revealed a positive and significant effect of environmental concern and literacy on attitudes toward the environment, as well as skills and knowledge on perceived behavioral control. Moreover, attitude towards the environment, subjective norms, and perceived behavioral control positively and significantly impacted beekeeping intention, which positively affected beekeeping startup behavior. The findings from the artificial neural network analysis revealed that the difference in the root mean square error values for training and testing was low, indicating a high level of predictive accuracy. Beekeeping facilitates income generation opportunities for low-income households, which may lead to increased household income and contribute to economic and ecological sustainability in Malaysia
Artificial neural network · Beekeeping · Partial least squares regression · Structural equation modeling · Sustainability · Theory of planned behavior · Environmental Education and Sustainability · Environmental Sustainability in Business · Social Acceptance of Renewable Energy
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| Citation velocity | historical |
|---|---|
| Highly cited | No |