Statistical modelling of travel mode choice of public university students in Freetown, Sierra Leone: the case of three campuses

Figures & data

Figure 1. Flowchart of the research methodology (Authors’ design).

Figure 2. Study area and sampling locations.

(Source: Authors’ concept)

Table 1. Model estimation parameters.

Variable	Description	Parameter Role
$AS{C}_{MBike}$	Alternative Specific Constant for motorbike	Mode Specific
$AS{C}_{Taxi}$	Alternative Specific Constant for taxi	Mode Specific
$AS{C}_{Keke}$	Alternative Specific Constant for keke	Mode Specific
$AS{C}_{NMT}$	Alternative Specific Constant for NMT	Mode Specific
$TT$	In-vehicle travel time (minutes)	Mode Specific
$TC$	Trip cost (SLL)	Mode Specific
$WT$	Bus stop waiting time (minutes)	Generic
$TD$	Travel distance (kilometers)	Mode Specific
$CO$	Comfort level	Mode Specific
$TF$	Trip frequency	Mode Specific
$GEN$	Gender	Mode Specific
$AGE$	Age (years)	Mode Specific
$TH$	Trip Hour	Mode Specific
$DEG$	Education Status	Mode Specific

Table 2. Attributes of respondents.

General Attributes	Frequency (number)	Percentage (%)
Gender
Female	289	45.7
Male	343	54.3
Age (years)
< 18	8	1.3
18–25	436	69
26–35	157	24.8
36–45	25	4.0
Above 45	6	0.9
Average household monthly income
< SLL500,000 (< $50)	249	39.4
SLL500,000 – SLL1,000,000 ($50–$100)	197	31.1
SLL1,000,000 – SLL5,000,000 ($100 - $500)	130	20.6
>SLL5,000,000 (> $500)	56	8.9
University College
Fourah Bay College - FBC	220	34.8
Institute of Public Administration and Management - IPAM	214	33.9
College of Medicine and Allied Health Sciences - COMAHS	198	31.3
Degree
Diploma	174	27.5
Certificate	18	2.9
Bachelor	433	68.5
Master	4	0.6
Other	3	0.5
Level
Year 1	281	45.0
Year 2	145	22.0
Year 3	99	16.0
Year 4	62	10.0
Year 5	10	2.0
Other	35	5.0
Driver’s License
Yes	68	10.8
No	564	89.2
Travel Distance (km)
<1	27	4.3
1–5	199	31.5
>5	406	64.2

Source: Authors’ field data.

$1 = SLL10,000 (Source: Bank of Sierra Leone exchange rate for June, 2021).

Figure 3. (a) Distribution of students’ modal share (Source: Authors’ field data) (b) Current motorized transport modal split in Freetown (Source: Statistics Sierra Leone, 2015; 2017).

Figure 4. (a) Graphical representation of transport modes (b) Distribution between university campus and preferred mode (Source: Authors’ field data).

Figure 5. Perception of importance level toward factors affecting transportation mode choice (Source: Authors’ field data).

Table 3. Model estimation output.

Parameter	PT Mode	Estimated Coefficient	SE	$t-test$	$p-value$
$\mathrm{A}\mathrm{S}{\mathrm{C}}_{\mathrm{M}\mathrm{B}\mathrm{i}\mathrm{k}\mathrm{e}}$	Motorbike	4.67	0.795	5.878	0.000
$\mathrm{A}\mathrm{S}{\mathrm{C}}_{\mathrm{T}\mathrm{a}\mathrm{x}\mathrm{i}}$	Taxi	4.38	0.834	5.252	0.000
$\mathrm{A}\mathrm{S}{\mathrm{C}}_{\mathrm{K}\mathrm{e}\mathrm{k}\mathrm{e}}$	Keke	3.50	0.884	3.952	0.000
$\mathrm{A}\mathrm{S}{\mathrm{C}}_{\mathrm{N}\mathrm{M}\mathrm{T}}$	NMT	2.91	2.042	1.427	0.154
$\mathrm{T}{\mathrm{C}}_{\mathrm{p}}$	Podapoda	−1.45	0.283	−5.100	0.000
$\mathrm{T}{\mathrm{D}}_{\mathrm{p}}$	Podapoda	1.55	0.262	5.911	0.000
$\mathrm{C}{\mathrm{O}}_{\mathrm{p}}$	Podapoda	0.29	0.092	3.156	0.002
$\mathrm{T}{\mathrm{T}}_{\mathrm{m}}$	Motorbike	−0.96	0.217	−4.413	0.000
$\mathrm{T}{\mathrm{C}}_{\mathrm{m}}$	Motorbike	−1.02	0.278	−3.683	0.000
$\mathrm{C}{\mathrm{O}}_{\mathrm{m}}$	Motorbike	−0.24	0.109	−2.229	0.026
$T{T}_T$	Taxi	−1.15	0.228	−5.070	0.000
$T{C}_T$	Taxi	−1.19	0.281	−4.252	0.000
$T{H}_T$	Taxi	−1.50	0.448	−3.342	0.001
$C{O}_T$	Taxi	0.26	0.095	2.740	0.006
$T{T}_k$	Keke	−0.69	0.241	−2.854	0.004
$T{C}_k$	Keke	−1.42	0.288	−4.916	0.000
$AG{E}_k$	Keke	0.73	0.201	3.614	0.000
$GE{N}_k$	Keke	−0.70	0.331	−2.102	0.036
$T{T}_n$	NMT	−2.15	0.456	−4.725	0.000
$T{D}_n$	NMT	−1.62	0.459	−3.543	0.000
$AG{E}_n$	NMT	−1.90	0.663	−2.870	0.004
$GE{N}_n$	NMT	1.76	0.672	2.621	0.009
$DE{G}_n$	NMT	1.18	0.432	2.740	0.006
$T{F}_n$	NMT	−0.54	0.278	−1.928	0.054
$WT$	Motorbike & Taxi	−0.30	0.107	−2.808	0.005
Model Statistics
Initial Log Likelihood		−770.921
Final Log Likelihood		−462.559
Likelihood Ratio Test		616.723
Rho-Square		0.400
AIC		969.656
BIC		1090.635

Source: Authors’ field data.

Table 4. Model prediction results.

	Predicted
Observed	Podapoda (75)	Motorbike (23)	Taxi (7)	Keke (2)	NMT (8)	% Accuracy	% Coverage
Podapoda (53)	51	0	0	1	1	96.2%	141.5%
Motorbike (34)	9	18	4	0	3	52.9%	67.6%
Taxi (10)	4	3	3	0	0	30.0%	70.0%
Keke (14)	11	1	0	1	1	7.1%	14.3%
NMT (4)	0	1	0	0	3	75%	200%
Market Shares	65.2%	20.0%	6.1%	1.7%	7.0%
Overall Prediction Accuracy						66.1%

Source: Authors’ field data.

Table 5. Aggregate elasticity of public transport modes.

Mode	% Change in probability of selecting a particular PT mode
	Minibus		Taxi		Three-wheeler		Two-wheeler		NMT
As a result of 1% change in	Travel cost	Travel time	Travel cost	Travel time	Travel cost	Travel time	Travel cost	Travel time	Trip distance
Cross Elasticity	1.240	-	0.810	0.210	0.770	0.160	-	-	-
Direct Elasticity	−4.860	-	−4.330	−1.560	−5.610	−0.840	−3.560	−1.230	−7.050

Source: Authors’ field data.

Figure 6. Factors that influence the choice of each PT mode (Source: Authors’ concept).

Data availability statement

The data presented in this study are available on request from the corresponding author.