Meeting European exporting certification standards as a sustainable marketing choice among mango farmers in Ghana

Figures & data

Figure 1. Conceptual framework.

Figure 2. Map of the study area.

Source: Authors’ own, 2022

Table 1. Description of variables used for regression analysis

Variable	Description	Type	Measurement	Model I	Model II	Mean	Std. Dev.	Supporting literature
Dependent variable
Choice of market outlet	Outlet via which farmers dispose of mangoes	Categorical	1 = Local market 2 = Retail market 3 = Processors			0.47 0.30 0.71	0.50 0.46 0.46
Practice EU standard	Farmers comply with EU standards and certification	Binary	1 = Yes 0 = No			0.94	0.23
Independent variables
Socio-economic characteristics
Age	Age of farmer	Continuous	Number		+	46.42	14.86	(Despotović et al., 2019)*; (Ajewole, 2010)**
Gender	Gender of farmer	Binary	1 = Male 2 = Female	+	+	0.45	0.50	(Despotović et al., 2019)*
Education	Farmer’s level of education	Continuous	Years	+	+	3.02	0.978	(Akrong, Mbogoh, Irungu et al., 2020)*; (Ajewole, 2010)**
Household size	Number of people in the household	Continuous	Number		+	5.55	2.52	(Kleemann et al., 2014)**
Experience	Years of mango farming	Continuous	Years	+	+	7.42	4.66	(Akrong, Mbogoh, Irungu et al., 2020)*; (Ajewole, 2010) **
Farm-level and institutional characteristics
Farm size	Acreages of mango plantation	Continuous	Number (acres)	+		7.42	5.30	(Maertens & Swinnen, 2009)
Ready market	Access to a ready market	Binary	1 = Yes 0 = No	+	+	0.06	0.24	(Muthini, 2015) *; (Laosutsan et al., 2019) **
Farm-level and institutional characteristics
Quantity	Quantity of harvest	Continuous	Number (tonnes)	+		38.61	25.84	(Ermias, 2021)*
Quality	Fresh fruit external feature quality after harvest	Interval scale	1 = Very low 2 = Low 3 = Neutral 4 = High 5 = Very high	+	+	4.54	0.68	(Laosutsan et al., 2019)
Credit access	Access to credit facilities	Binary	1 = Yes 0 = No	+	+	0.33	0.47	(Muthini, 2015)*; (Kersting & Wollni, 2012) **
GAP	Proper use of agrochemicals and farm sanitation	Binary	1 = Yes 0 = No	+	+	0.64	0.47	(Opoku et al., 2020) *
Farm income	Annual farm income	Continuous	Number (GH¢)		+	2955.86	5266.09	(Akrong, Mbogoh, Irungu et al., 2020) **
Training	Received training on GAP	Binary	1 = Yes 0 = No		+	0.75	0.43	(Meemken et al., 2016) **

The dependent variable for Model I* reference is practice EU standards, and Model II* reference (Base market outlet = Processors) is the choice of marketing outlet. NB: 1US{{footpara}}amp;#x00A0;= GH¢5.73

Table 2. Demographic characteristics of respondents

Variable	Wenchi Municipal (N = 203)		Kintampo Municipal (N = 97)		Pooled (N = 300)
	No.	%	No.	%	No.	%
Gender
Male	110	54.2	54	55.7	164	54.7
Female	93	45.8	43	44.3	136	45.3
Age
20–30	45	22.1	8	8.2	53	17.7
31–40	54	26.6	14	14.4	68	22.7
41–50	33	16.3	19	19.6	52	17.2
51–60	381	18.7	28	28.9	66	22
>60	33	16.3	28	28.9	61	20.3
Educational level
Basic	24	11.8	2	2.1	48	26.5
Technical	66	32.5	50	51.5	15	8.3
Secondary	58	28.6	8	8.2	96	53
Tertiary	55	27.1	37	38.1	22	12.2
Marital status
Single	54	70	17	17.5	71	23.7
Married	142	26.6	70	72.2	212	70.7
Divorced	7	3.4	10	10.3	17	5.6
Household size
1–3	119	58.6	49	50.5	168	56
4–6	78	38.4	46	47.4	124	41.3
>6	6	3	2	2.1	8	2.7
Main occupation
Farming	186	91.6	78	80.4	264	88
Otherwise	17	8.4	19	19.6	36	12
Farm size
1–3	115	56.7	43	44.3	158	52.7
4–6	66	32.5	34	35.1	100	33.3
Above 6	22	10.8	20	20.6	42	14
Experience
1–5	98	48.3		32	129	43
6–10	88	43.3	33	34	121	40.3
11–15	14	6.9	18	18.6	32	10.7
>15	3	1.5	15	15.5	18	6
Off-farm job
Yes	125	61.6	56	57.7	166	55.3
No	78	38.4	41	42.3	134	44.7
Marketing channel choices
Local	79	38.92	16	16.49	95	31.67
Retail	49	24.14	12	12.37	61	20.33
Processing	75	36.95	69	71.13	144	48.00

Table 3. Motivation towards compliance with European Union standards

Variable	Strongly agree (5)	Agree (4)	Neutral (3)	Disagree (2)	Strongly disagree (1)	Mean	SD
Compliance ensures more profit	150(50.0)	125(41.7)	21(7.0)	4(1.3)	0(0)	4.40	0.68
Compliance ensures quality fruit	179(59.7)	112(37.3)	4(1.3)	1(0.3)	4(1.3)	4.54	0.68
Compliance guarantees a ready market	11(3.7)	7(2.3)	16(5.3)	117(39.0)	149(49.7)	1.71	0.95
Compliance augments credit access	49(16.3)	50(16.7)	86(28.7)	52(17.3)	63(21.0)	2.90	1.35

NB: Numbers in parentheses are percentages.

Table 4. Farmers’ willingness to comply with European Union practices

Variable	Very ready (5)	Ready (4)	Neutral (3)	Not ready (2)	Very not ready (1)	Mean	SD
Ready to ensure no chemical residues in the fruits	20(6.7)	21(7.0)	62(20.7)	102(34.0)	95(31.7)	2.23	1.16
Ready to ensure worker’s health and safety	11(3.7)	57(19.0)	94(31.3)	105(35.0)	33(11.0)	2.69	1.02
Willingness to ensure proper soil management	39(13.0)	113(37.7)	109(36.3)	33(11.0)	6(2.0)	3.49	0.92
Ready to optimise the use of chemical fertilizer	4(1.3)	22(7.3)	91(30.3)	123(41.0)	60(20.0)	2.29	0.91
Willing to practice integrated pest management	1(0.3)	8(2.7)	54(18.0)	120(40.0)	116(38.7)	1.86	0.83
Ready to utilise EU-approved chemicals	5(1.7)	5(1.7)	24(8.0)	127(42.3)	139(46.3)	1.70	0.82
Willing to fund the cost of certification	47(15.7)	47(15.7)	49(16.3)	61(20.3)	96(32.0)	2.60	1.45
Willing to adopt proper farm record keeping	2(0.7)	2(0.7)	38(12.7)	72(24.0)	186(62.0)	1.54	0.79
Willing to practice farm sanitation at all times	2(0.7)	0(0)	9(3.0)	135(45.0)	154(51.3)	1.53	0.62
Willing for farm to be certified by PPRSD	10(3.3)	26(8.7)	19(6.3)	166(55.3)	79(26.3)	2.07	0.99

NB: Numbers in parentheses are percentages, PPD = Plant Protection and Regulatory Services Directorate, and EU = European Union.

Table 5. Determinants of compliance with EU standards and certification practice among Mango producers

Variables	Coefficient	Robust Std. errs.	P-value	Marginal effects
Socio-economic characteristics
Age	0.007	0.009	0.428	0.001
Gender	−0.198	0.191	0.300	−0.039
Education	0.217	0.100	**0.031	0.423
Household size	−0.048	0.051	0.342	−0.009
Farm size	0.049	0.020	**0.015	0.797
GAP	0.182	0.093	**0.050	0.035
Experience	−0.213	0.202	0.292	−0.041
Institutional characteristics
Farm income	−0.213	0.097	**0.027	−0.041
Quality fruits	−0.095	0.119	0.427	−0.018
Ready market	0.340	0.132	***0.010	0.066
Standard training	−0.371	0.113	***0.001	−0.072
Credit access	0.095	0.082	0.242	0.019
Constant	0.989	0.799	0.216
Prob >Chi^2	0.002
Wald Chi^2 (12)	30.07
Pseudo R^2	0.790
Log pseudo-likelihood	106.262

Note: ***, **, and * represent significance levels at 1%, 5%, and 10%, respectively. NB: 1US{{footpara}}amp;#x00A0;= GH¢5.73

Table 6. Drivers of Mango producers’ Mango outlet preference

	Local market				Retail market
Variables	Co-eff.	Robust Std. Err	P-Values	Marginal Effect	Co-eff.	Robust Std. Err	P-Values	Marginal Effects
Socio-demographic characteristics
Age	−1.171	0.566	**0.039	−0.024	−0.797	0.527	0.130	−0.002
Gender	0.597	0.366	*0.103	0.059	0.296	0.348	0.395	0.039
Education	−0.238	0.206	0.247	−0.294		0.189	0.654	−0.168
Experience	0.123	0.048	***0.010	0.014	0.158	0.047	*0.001	0.005
Farm-level and institutional characteristics
Farm size	0.037	0.035	0.295	0.020	0.024	0.031	0.445	0.003
Ready market	1.673	0.413	***0.000	0.012	1.277	0.400	***0.001	0.020
Quantity	0.180	0.426	0.673	0.258	0.984	0.567	*0.083	0.191
Quality	0.243	0.160	0.129	0.078	−0.240	0.146	*0.101	0.042
GAP	−0.199	0.175	0.257	−0.059	−0.331	0.143	**0.021	−0.058
Credit access	0.100	0.136	0.461	0.0681	0.337	0.105	***0.001	0.523
Constant	1.808	1.506	0.230		2.007	1.710	0.241
Base category Processors
Wald chi2 (22)		38.04
Prob>chi2		0.000***
PseudoR^2		0.061
Log pseudo Likelihood		−293.123

Note: ***, **, and * represent significance levels at 1%, 5%, and 10%, respectively.

Despotović, M. A., Rodić, J., & Caracciolo, F. (2019). Factors affecting farmers’ adoption of integrated pest management in Serbia: An application of the theory of planned behavior. Journal of Cleaner Production, 228, 1196–1205. https://doi.org/10.1016/j.jclepro.2019.04.149

 Web of Science ®Google Scholar

Ajewole, O. C. (2010). Farmers response to adoption of commercially available organic fertilisers in Oyo state, Nigeria. African Journal of Agricultural Research, 5(18), 2497–2503. http://www.academicjournals.org/AJAR

 Google Scholar

Akrong, R., Mbogoh, S. G., & Irungu, P. (2020). Youth agripreneurship in the horticultural value‐chain: The case of small‐scale Mango farmers in Southern Ghana. African Development Review, 32(S1), S68–S77. https://doi.org/10.1111/1467-8268.12483

 Google Scholar

Kleemann, L., Abdulai, A., & Buss, M. (2014). Certification and access to export markets: Adoption and return on investment of organic-certified pineapple farming in Ghana. World Development, 64, 79–92. https://doi.org/10.1016/j.worlddev.2014.05.005

 Web of Science ®Google Scholar

Maertens, M., & Swinnen, J. F. M. (2009). Trade, standards, and poverty: Evidence from Senegal. World Development, 37(1), 161–178. https://doi.org/10.1016/j.worlddev.2008.04.006

 Web of Science ®Google Scholar

Muthini, D. N. (2015). An assessment of mango farmers’ choice of marketing channels in Makueni, Kenya. Masters Dissertation, University of Nairobi-Kenya

 Google Scholar

Laosutsan, P., Shivakoti, G. P., & Soni, P. (2019). Factors influencing the adoption of good agricultural practices and export decision of Thailand’s vegetable farmers. International Journal of the Commons, 13(2), 867–880. https://doi.org/10.5334/ijc.895

 Web of Science ®Google Scholar

Ermias, D. (2021). Econometric analysis of factors affecting market outlet choice of Mango fruit producers in Hadero Tunto Zuriya District, Southern Ethiopia. Cogent Food & Agriculture, 7(1), 1891660. https://doi.org/10.1080/23311932.2021.1891660

 Web of Science ®Google Scholar

Kersting, S., & Wollni, M. (2012). New institutional arrangements and standard adoption: Evidence from small-scale fruit and vegetable farmers in Thailand. Food Policy, 37(4), 452–462. https://doi.org/10.1016/j.foodpol.2012.04.005

 Web of Science ®Google Scholar

Opoku, P. D., Bannor, R. K., & Oppong-Kyeremeh, H. (2020). Examining the willingness to produce organic vegetables in the Bono and Ahafo Regions of Ghana. International Journal of Social Economics, 47(5), 619–641. https://doi.org/10.1108/IJSE-12-2019-0723

 Web of Science ®Google Scholar

Meemken, E.-M., Veettil, P. C., & Qaim, M. (2016). Small farmers’ preferences for the design of certification schemes: Does gender matter? Global Food Discussion Papers. Georg-August-Universität Göttingen, Research Training Group (RTG) 1666 - GlobalFood, Göttingen.

 Google Scholar

Data availability statement

Data will be made available upon request from the corresponding author.