Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya
The purpose of this study was to identify the underlying socio-psychological factors that influence pond and cage farmers’ intentions to adopt Black Soldier Fly Larvae (BSFL) in Kenya. Based on the Technology Acceptance Model (TAM), this study empirically investigated the relationship between TAM co...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | All Life |
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| Online Access: | http://dx.doi.org/10.1080/26895293.2022.2112765 |
| _version_ | 1797236914392137728 |
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| author | Kevin Okoth Ouko Adrian Wekulo Mukhebi Kevin Odhiambo Obiero Florence Achieng Opondo |
| author_facet | Kevin Okoth Ouko Adrian Wekulo Mukhebi Kevin Odhiambo Obiero Florence Achieng Opondo |
| author_sort | Kevin Okoth Ouko |
| collection | DOAJ |
| description | The purpose of this study was to identify the underlying socio-psychological factors that influence pond and cage farmers’ intentions to adopt Black Soldier Fly Larvae (BSFL) in Kenya. Based on the Technology Acceptance Model (TAM), this study empirically investigated the relationship between TAM constructs, namely Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude towards Use (ATT), and Behavioral Intention (BI) to use BSFL. The study used a cross-sectional survey design to collect primary data from 211 randomly selected cage operators (98) and pond farmers (113) in Kenya’s Siaya, Kisumu, and Homabay Counties. A structural equation model was employed to examine hypothesized paths in the uptake of BSFL meal with the aid of SmartPLS 3. The inner model path coefficients suggested that ATT had the strongest effect on farmers’ intentions to adopt BSFL (0.411). Further, PU had a greater relative influence on intention to adopt BSFL than PEOU based on the model path coefficients of 0.319 and 0.178 respectively. This indicates that the more respondents believe BSFL is useful in their fish farm's production conditions, the more likely they are to adopt BSFL. Consequently, these findings have direct implications for policy development and the potential use of BSFL in aquaculture. |
| first_indexed | 2024-03-08T16:58:36Z |
| format | Article |
| id | doaj.art-2cab1cc1576a4782a76bd6e4863e1362 |
| institution | Directory Open Access Journal |
| issn | 2689-5307 |
| language | English |
| last_indexed | 2024-04-24T17:11:25Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | All Life |
| spelling | doaj.art-2cab1cc1576a4782a76bd6e4863e13622024-03-28T09:48:50ZengTaylor & Francis GroupAll Life2689-53072022-12-0115188490010.1080/26895293.2022.21127652112765Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in KenyaKevin Okoth Ouko0Adrian Wekulo Mukhebi1Kevin Odhiambo Obiero2Florence Achieng Opondo3Jaramogi Oginga Odinga University of Science and TechnologyJaramogi Oginga Odinga University of Science and TechnologySangoro Aquaculture Research Station, Kenya Marine and Fisheries Research InstituteSchool of Business and Economics, Laikipia UniversityThe purpose of this study was to identify the underlying socio-psychological factors that influence pond and cage farmers’ intentions to adopt Black Soldier Fly Larvae (BSFL) in Kenya. Based on the Technology Acceptance Model (TAM), this study empirically investigated the relationship between TAM constructs, namely Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Attitude towards Use (ATT), and Behavioral Intention (BI) to use BSFL. The study used a cross-sectional survey design to collect primary data from 211 randomly selected cage operators (98) and pond farmers (113) in Kenya’s Siaya, Kisumu, and Homabay Counties. A structural equation model was employed to examine hypothesized paths in the uptake of BSFL meal with the aid of SmartPLS 3. The inner model path coefficients suggested that ATT had the strongest effect on farmers’ intentions to adopt BSFL (0.411). Further, PU had a greater relative influence on intention to adopt BSFL than PEOU based on the model path coefficients of 0.319 and 0.178 respectively. This indicates that the more respondents believe BSFL is useful in their fish farm's production conditions, the more likely they are to adopt BSFL. Consequently, these findings have direct implications for policy development and the potential use of BSFL in aquaculture.http://dx.doi.org/10.1080/26895293.2022.2112765black soldier fly larvaenile tilapiapartial least squaresstructural equation modeltechnology acceptance model |
| spellingShingle | Kevin Okoth Ouko Adrian Wekulo Mukhebi Kevin Odhiambo Obiero Florence Achieng Opondo Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya All Life black soldier fly larvae nile tilapia partial least squares structural equation model technology acceptance model |
| title | Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya |
| title_full | Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya |
| title_fullStr | Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya |
| title_full_unstemmed | Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya |
| title_short | Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya |
| title_sort | using technology acceptance model to understand fish farmers intention to use black soldier fly larvae meal in nile tilapia production in kenya |
| topic | black soldier fly larvae nile tilapia partial least squares structural equation model technology acceptance model |
| url | http://dx.doi.org/10.1080/26895293.2022.2112765 |
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