Using technology acceptance model to understand fish farmers’ intention to use black soldier fly larvae meal in Nile tilapia production in Kenya

Figures & data

Figure 1. Research model illustrating the hypothetical influence of technology acceptance factors on intentions to use BSFL in fish farming.

Table 1. Distribution of respondents by farmer category per county.

	County
Farmer Category	Siaya	Kisumu	Homabay	Total
Fish pond farmer	45	33	35	113
Cage farmer	35	34	29	98
Total	80	67	64	211

Note: Survey (2021).

Table 2. Fish Farmer Socio-economic profile for categorical variables.

Categorical Variables	Frequency (n)	Percent (%)
Category of fish farmer
Fish pond farmer	113	53.6
Cage farmer	98	46.4
Gender
Female	55	26.1
Male	156	73.9
Education level
Primary level	40	19.0
Secondary level	110	52.1
University level	61	28.9
Reasons for fish farming
Commercial	199	94.3
Subsistence	12	5.7
Occupation
Farming	114	54.0
Off-farm business	65	30.8
Salaried	32	15.2
Access to credit
No	129	61.1
Yes	82	38.9
Access to extension services
Yes	92	43.6
No	119	56.4
Group membership
No	170	80.6
Yes	41	19.4

Table 3. Fish Farmer Socio-economic profile for continuous variables.

Continuous Variables	Minimum	Maximum	Mean	Std. Deviation
Age in years of respondent	19	82	43.04	11.674
Years of farming experience	1	12	3.65	2.412
Stocking density per pond/cage in m^2	100	25,000	3664.69	5606.955
Number of ponds/cages owned	1	195	7.53	20.378
Distance to feeds source in Km	1	800	52.52	103.042
Number of times of feeding in a day	1	4	1.93	.923

Figure 2. Indicator loadings and path coefficients of key behavioral constructs.

Table 4. Internal consistency: Cronbach's Alpha, composite reliability, and average variance extracted.

Latent Variable	Cronbach's Alpha	Composite reliability (CR)	Average variance extracted (AVE)
Attitude	0.811	0.888	0.726
Intention to use	0.786	0.876	0.704
Perceived ease of use	0.701	0.831	0.625
Perceived usefulness	0.684	0.823	0.610

Cutoff levels: Cronbach’s alpha > 0.7 (0.6); composite reliability (CR) = 0.6–0.9; Average Variance Extracted (AVE) > 0.5; n = 211.

Table 5. Fornell-Larcker criterion analysis for checking discriminant validity.

	Attitude	Intention to Use	Perceived Ease of Use	Perceived Usefulness
Attitude	0.852
Intention to Use	0.724	0.839
Perceived Ease of Use	0.579	0.57	0.79
Perceived Usefulness	0.657	0.675	0.482	0.781

Note: Values on the diagonal (bolded) are the square root of the average variance extracted (AVE) while the off diagonals are correlations.

Table 6. Heterotrait-Monotrait (HTMT) criterion.

	Attitude	Intention to Use	Perceived Ease of Use	Perceived Usefulness
Attitude
Intention to Use	0.900
Perceived Ease of Use	0.745	0.754
Perceived Usefulness	0.866	0.882	0.651

Note: Cut-off level: HTMT < 0.9.

Figure 3. Bootstrapping results showing t-statistics.

Table 7. Results of path coefficients and hypothesis testing, n = 211.

Path correlation	Path coefficients	T Statistics^a	P Values	Ho Support
Direct Effects
Perceived Ease of Use – > Attitude (H1)	0.341***	6.268	0.000	Supported
Perceived Ease of Use – > Intention to Use (H2)	0.178**	2.900	0.004	Supported
Perceived Usefulness – > Attitude(H3)	0.492***	9.739	0.000	Supported
Perceived Usefulness – > Intention to Use (H4)	0.319***	4.577	0.000	Supported
Attitude – > Intention to Use (H5)	0.411***	5.686	0.000	Supported
Specific Indirect Effects
Perceived Ease of Use – > Attitude – > Intention to Use (H6)	0.140***	4.050	0.000	Supported
Perceived Usefulness – > Attitude – > Intention to Use(H7)	0.202***	4.493	0.000	Supported

***p< 0.01, **p< 0.05; ^acalculated by bootstrapping (5000 subsamples); Attitude R²=  0.516; Intention to use R²=  0.614; Attitude Q²=  0.370; Intention to Use Q²=  0.424.

Table A1. Latent variables, indicator ID and the corresponding questionnaire statements used within the survey.

Indicator	Item Measure	References	Scale (1–5)	Mean	SD
PEOU1	Improve the sustainability of fish production	Chia et al. (2019)	Strongly disagree – Strongly agree	3.70	1.000
PEOU2	Improve the societal acceptance in fish farming	Verbeke et al. (2015)	Strongly disagree – Strongly agree	3.05	1.216
PEOU3	Lower the ecological footprint of livestock farming	Chaalala et al. (2018)	Strongly disagree – Strongly agree	1.87	.884
PEOU4	Allow farmers produce high quantities of fish for the world population	Verbeke et al. (2015)	Strongly disagree – Strongly agree	2.21	.893
PEOU5	Lower production cost in fish farming without fish reducing quality	Sinansari and Fahmi (2020)	Strongly disagree – Strongly agree	1.39	.587
PEOU6	Decrease the overexploitation of water bodies	Tiu (2012)	Strongly disagree – Strongly agree	1.87	1.079
PEOU7	Lower our dependence on foreign protein sources	Verbeke et al. (2015)	Strongly disagree – Strongly agree	1.68	.827
PEOU8	Lower the cost of Fish feed	Verbeke et al. (2015)	Strongly disagree – Strongly agree	1.33	.555
PEOU9	Lower our dependence on imported feed	Verbeke et al. (2015)	Strongly disagree – Strongly agree	1.52	.764
PEOU10	Improve organic waste management in the country	Dicke (2018)	Strongly disagree – Strongly agree	1.36	.619
PU1	Use of BSFL feed is a system easy to understand	Oppong (2017)	Strongly disagree – Strongly agree	1.78	1.105
PU2	Use of BSFL is a system that would be easy to implement on my fish farm.	Rana et al. (2015)	Strongly disagree – Strongly agree	2.00	1.229
PU3	Using BSFL meal would enhance my effectiveness on fish production	Mulumpwa (2018)	Strongly disagree – Strongly agree	2.34	1.271
PU4	Using BSF meal will improve my fish production efficiency	Roffeis et al. (2018)	Strongly disagree – Strongly agree	2.19	1.208
ATT1	BSFL provide cheap source of protein in fish farming	Higa et al. (2021)	Strongly disagree – Strongly agree	1.35	.517
ATT2	BSFL Provide nutrients and minerals	Makkar et al. (2014)	Strongly disagree – Strongly agree	1.96	.930
ATT3	Possibility of rearing BSF guarantees availability	Yildirim-Aksoy et al. (2020)	Strongly disagree – Strongly agree	2.21	1.255
ATT4	Rearing BSF requires small space and is cost effective	Van Huis et al. (2013)	Strongly disagree – Strongly agree	1.36	.726
ATT5	BSF has low feeding costs because it feed on wastes thus cleans environment	Dicke (2018)	Strongly disagree – Strongly agree	1.32	.552
ATT6	Hard to create awareness and promote BSFL meal to people based on legislative issues	Belghit et al. (2019)	Strongly disagree – Strongly agree	3.27	1.157
ATT7	Long time required to change attitudes of people to consider BSFL meal as feed.	Kelemu et al. (2015)	Strongly disagree – Strongly agree	2.99	1.123
INT1	I intend to use BSFL in my fish farm	Ssepuuya et al. (2019)	Unlikely-likely	1.83	1.229
INT2	I would recommend the adoption of BSFL meal for other fish farmers in my region	Domingues et al. (2020)	Unlikely-likely	1.68	1.238
INT3	I would also adopt BSFL meal if the neighboring farmers adopt	Joffre et al. (2020)	Unlikely-likely	1.59	1.132

Table A2. Test for common method bias.

Total variance explained
	Initial eigenvalues			Extraction sums of squared loadings
Component	Total	% of variance	Cumulative %	Total	% of variance	Cumulative %
1	7.476	31.150	31.150	7.476	31.150	31.150
2	2.262	9.426	40.575
3	1.885	7.855	48.430
4	1.373	5.719	54.149
5	1.293	5.389	59.538
6	1.150	4.793	64.331
Extraction Method: Principal Component Analysis.

Table A3. Variance inflation factor (VIF) values.

Variable	VIF
ATT1	1.64
ATT2	1.825
ATT3	1.954
INT1	1.339
INT2	2.166
INT3	2.351
PEOU1	1.397
PEOU2	1.688
PEOU3	1.322
PU10	1.365
PU3	1.364
PU7	1.277
Attitude	2.087
Perceived Usefulness	1.545
Perceived Ease of Use	1.808

Table A4. Outer loadings (factor loadings).

Factor/Indicator	Attitude	Intention to Use	Perceived Ease of Use	Perceived Usefulness
ATT1 BSFL provide cheap source of protein in fish farming	0.818
ATT2 BSFL Provide nutrients and minerals	0.855
ATT3 Possibility of rearing BSF guarantees availability	0.882
INT1, I intend to use BSFL in my fish farm		0.731
INT2 I would recommend the adoption of BSFL meal for other fish farmers in my region		0.877
INT3 I would also adopt BSFL meal if the neighboring farmers adopt		0.898
PEOU1 Use of BSFL feed is a system easy to understand			0.794
PEOU2 Use of BSFL is a system that would be easy to implement on my fish farm			0.89
PEOU3 Using BSFL meal would enhance my effectiveness on fish production			0.673
PU10 Improve organic waste management in the country				0.801
PU3 Lower the ecological footprint of livestock farming				0.835
PU7 Lower our dependence on foreign protein sources				0.700

Source: Field survey (2021).

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Data availability

The data that support the findings of this study are openly available in Figshare at https://doi.org/10.6084/m9.figshare.19739023.