An assessment of the impact of disaster risks on dairy supply chain performance in Zimbabwe

Figures & data

Table 1. Demographic data

Biographical data	Variable	Frequency	Percentage
Gender	Male	67	84.81
	Female	12	15.19
Age	31 ≤ Age ≤ 40	8	10.13
	41 ≤ Age ≤ 50	12	15.19
	51 ≤ Age ≤60	33	41.77
	Age ≥ 61	26	32.91
Level of education	Ordinary level	14	17.72
	Diploma	47	59.49
	Degree	12	15.19
	Postgraduate	6	7.59
Region	Chipinge	9	11.39
	Gweru	18	22.78
	Harare	25	31.65
	Bulawayo	17	21.52
	Mutare	10	12.66
Experience	0 ≤ Experience ≤ 5	7	8.86
	6 ≤ Experience ≤ 10	38	48.10
	11 ≤ Experience ≤ 15	22	27.85
	Experience ≥ 16	12	15.19

Source: author.

Table 2. OLS estimates: Impact of disaster risks on job losses, food security, hindrance growth and milk productivity

Variables	(1)	(2)	(3)	(4)
	Job loss	Food insecurity	Hindered growth	Reduced Productivity
Disaster risks	0.0797*	0.0903**	0.0525**	0.0413*
	(0.0409)	(0.0375)	(0.0252)	(0.0247)
Gender	0.133	0.337	0.330***	−0.00752
	(0.151)	(0.205)	(0.102)	(0.169)
Age	−0.104	−0.114	0.0147	−0.0438
	(0.0627)	(0.0689)	(0.0519)	(0.0520)
Level of education	−0.112	−0.130	−0.0659	0.0520
	(0.0851)	(0.100)	(0.0860)	(0.0724)
Experience	−0.0695	0.0697	−0.0359	−0.156**
	(0.0735)	(0.0861)	(0.0773)	(0.0589)
Chipinge	−0.103	0.188	−0.0126	−0.366**
	(0.168)	(0.176)	(0.220)	(0.156)
Gweru	0.0879	0.391**	0.0340	−0.151
	(0.204)	(0.188)	(0.201)	(0.180)
Harare	0.416	0.731**	0.327	0.0776
	(0.320)	(0.290)	(0.258)	(0.236)
Bulawayo	0.0850	−0.00265	0.0540	−0.0428
	(0.214)	(0.200)	(0.206)	(0.190)
Constant	1.450	0.308	1.731	2.999**
	(1.810)	(1.749)	(1.203)	(1.159)
Observations	77	77	77	77
R^2	0.237	0.214	0.168	0.214

Note: Robust standard errors in parentheses.

* p < 0.1.

** p < 0.05.

*** p < 0.01.

Table

Male	01
Female	02

Table

18–24	01
25–30	02
31–40	03
41–50	04
51–60	05
60+	06

Table

O Level	01
Diploma	02
Degree	03
Post Graduate	04

Table

Chipinge	01
Gweru	02
Harare	03
Bulawayo	04
Mutare	05
Other	06

Table

0–5 years	01
6–10 years	02
11–15 years	03
16 and above	04

Table

SECTION B: Supply chain risks affecting dairy industry	Strongly disagree	Disagree	Uncertain	Agree	Strongly agree
6. High interest rates	1	2	3	4	5
7.Local dairy giants flexing financial muscle	1	2	3	4	5
8. Unfair competition from foreign dairy brands	1	2	3	4	5
9.Government policy inconsistency in agricultural sector	1	2	3	4	5
10. Political interferences	1	2	3	4	5
11.Droughts	1	2	3	4	5
12.Cattle diseases	1	2	3	4	5
13. Cyclones	1	2	3	4	5
14. Extreme cold weather conditions	1	2	3	4	5
15. Food Processing facilities	1	2	3	4	5
16.Power outages	1	2	3	4	5
17. Milking machinery	1	2	3	4	5
18.High labour costs	1	2	3	4	5
19. High cost of breeding herd	1	2	3	4	5

Table

Section C: Impact of disaster risks on dairy supply chain performance	Strongly Disagree	Disagree	Uncertain	Agree	Strongly agree
20. Natural disasters have killed the livelihoods of the farming community through job losses	1	2	3	4	5
21. Disasters plaguing the dairy industry are threatening food security	1	2	3	4	5
22. Depletion of dairy herd making it hard for farmers to adequately supply milk to feed Zimbabwe and export milk	1	2	3	4	5
23. Disasters in the dairy industry are exposing local dairy companies to fierce competition thereby hindering growth of infant industries	1	2	3	4	5
24.The quality of milk has deteriorated owing to the low quality of pastures and stock feeds	1	2	3	4	5
25. The decline in milk output has led to the closure of some processing plants	1	2	3	4	5
26. The low milk output has led in a decline in foreign currency earnings	1	2	3	4	5