Use of latent variables representing psychological motivation to explore citizens’ intentions with respect to congestion charging reform in Jakarta

Figures & data

Figure 1. (a) Jakarta region; (b) ERP charging zone (SITRAMP, 2004).

Table 1. Summary of SC experiment.

Descriptions
Time of survey	17 November–3 December 2013
Target location	Central Jakarta and part of south Jakarta
Distribution methods	Direct interviews and collected by enumerator
Number of questionnaires distributed	2100 questionnaires
Number of questionnaires returned	1998 (95.1%) questionnaires
Questionnaire patterns
Pattern 1 charge	10,000 IDR
Pattern 2 charge	21,000 IDR
Pattern 3 charge	35,000 IDR
Days of week collected sample’s share
Weekdays (weekends)	71% (29%)

Table 2. Summary of question categories in questionnaire survey.

No.	Category	Description
1	Visitor mobility characteristics	Purpose of trip, number of accompanying persons, and mode choices
2	General opinion of ERP, traffic congestion and the environment. Respondents were asked to choose among four responses to road pricing:	Recognition, acceptability, and fairness of ERP
		Inhibition of freedom of movement by ERP
		Consequences of ERP implementation Opinion on present level of urban transport services
	1. well accepted
	2. accepted
		Opinion on city center transport and environment
	3. not accepted
		Extent of recognition of environmental issues
	4. not accepted at all
		Opinion on government policies
		Opinion on use of income from ERP
3	Respondent’s mobility responses to introduction of road pricing charge scenarios	Awareness of possible different visit behavior on day of survey under different charge schemes
4	Individual socio-demographic characteristics	Gender, age, driver’s license, employment status, annual income
5	Daily mobility attitudes and responses to ERP proposal	Trip purpose, mode choices, frequency of using private modes, frequency of using transit, and frequency of visits to the CBD (in a week)

Table 3. Summary of respondents’ demographics.

Item	Category	Frequency	Percentage (%)
Age	Under 20	183	11.1
	20 to 29	819	49.9
	30 to 39	421	25.6
	40 to 49	168	10.2
	50 and older	51	3.1
Gender	Male	852	51.9
	Female	789	48.1
Employment status	Working	1132	69.0
	Student	418	25.4
	Housewife	67	4.1
	Not working	24	1.4
Annual household income	Below 3.6 million IDR	308	18.7
	3.6–6 million IDR	360	22.0
	6–9 million IDR	358	21.8
	9–12 million IDR	174	10.6
	12–18 million IDR	225	13.7
	18–24 million IDR	91	5.5
	24–30 million IDR	73	4.4
	30–36 million IDR	21	1.3
	36 million IDR or more	32	2.0

Table 4. Summary of respondents’ daily mobility habits.

Item	Category	Frequency	Percentage (%)
Driver’s license	Yes	1156	70.5
	No	485	29.5
Travel mode used on the day of the questionnaire survey	Public transit	813	49.57
	Private mode	828	50.43
Purpose of visiting the target area of the ERP scheme (CBD)	Work	793	48.35
	Meetings and sales	29	1.77
	Delivery	8	.49
	Trader	52	3.17
	Shopping	285	17.38
	Entertainment and eating	174	10.61
	Studying and lessons	162	9.88
	School	27	1.65
	Out for a walk/drive	110	6.71
Frequency of visits to the target area of the ERP scheme (CBD)	More than 5 days a week	761	46.3
	3–4 days a week	274	16.7
	1–2 days a week	206	12.6
	2–3 days a month	213	13.0
	1 day a month or less	187	11.4
Frequency of car usage in daily life	More than 5 days a week	665	40.5
	3–4 days a week	250	15.2
	1–2 days a week	178	10.8
	2–3 days a month	188	11.4
	1 day a month or less	361	22.0

Table 5. Description and empirical setting of latent variables, indicators, and causes.

Var.	Description, variable setting
Latent psychological motivations
ARP	Appropriateness of ERP adoption
REP	Recognition that ERP can mitigate congestion and improve the environment
CDC	Car dependency
APC	Awareness of the problems of cars in society
AFM	Inhibition of freedom movement caused by ERP
DEP	Doubts about the ability of ERP to mitigate congestion and environment problems
Observed psychological motivation-related questions (indicators)
CRP	ERP is correct policy, 1 = quite right, 4 = totally wrong
ACP	ERP will be accepted by the public, 1 = well accepted, 4 = not accepted at all
FRP	ERP is a fair policy, 1 = quite fair, 4 = quite unfair
ICG	ERP should be implemented to improve congestion, 1 = quite agree, 4 = totally disagree
IGW	ERP should be implemented to mitigate global warming (GM), 1 = quite agree, 4 = totally disagree
MCG	ERP can mitigate congestion, 1 = much result, 4 = no result at all
MEP	ERP can mitigate environmental problems, 1 = much result, 4 = no result at all
CNL	A car is absolutely necessary in daily life, 1 = quite necessary, 4 = quite unnecessary
PNL	Public transit (PT) is absolutely necessary in daily life, 1 = quite necessary, 4 = quite unnecessary
PAV	PT is easy and convenient to use, 1 = quite easy, 4 = quite hard
TCG	Traffic is congested in the CBD, 1 = quite congested, 4 = no congested at all
PED	The pedestrian environment is dangerous, 1 = quite dangerous, 4 = quite safe
CGW	Cars are the major cause of global warming, 1 = quite agree, 4 = totally disagree
IFD	ERP can impede the freedom to drive, 1 = no impediment at all, 4 = much impediment
IFM	ERP can impede the freedom of movement, 1 = no impediment at all, 4 = much impediment
CNV	ERP will affect the number visitors to the CBD, 1 = much more, 4 = much less
DCU	ERP will decrease car use, 1 = not decrease at all, 4 = much decrease
IPU	ERP will increase PT use, 1 = not increase at all, 4 = much increase
DFV	ERP would decrease or increase your visits to the CBD, 1 = not decrease at all, 4 = much increase
Socio-demographics (causes)
GD	Gender, dummy variable with 1 if male, 0 otherwise
AG	Age, dummy variable with 1 ≥ 40 years, 0 otherwise
AI	Annual income, numerical ≤3.6 million IDR to ≥36 million IDR
ES	Employment status, dummy variable with 1 if employed, 0 otherwise

Figure 2. MIMIC model estimation result with ellipses represent latent variables, arrows represent paths significant at the 5% level.

Table 6. Ordinal preferences of public acceptance of ERP proposal.

Category	Freq.	Percent	Cumulative
1. Well accepted	153	9.33	9.33
2. Accepted	879	53.6	62.93
3. Not accepted	545	33.23	96.16
4. Not accepted at all	63	3.84	100.00

Table 7. Description of explanatory variables.

Variable	Description	Mean	Std. dev.
Levy rate patterns
LR	Scenarios; 10,000 to 35,000 IDR	24,836	10,439
Latent constructs
ARP	Appropriateness of ERP adoption; numerical	.0477	.105
REP	Recognition effect of ERP; numerical	.0471	.100
CDC	Car dependency; numerical	.0268	.067
APC	Awareness of problem of cars; numerical	.0350	.011
AFM	Inhibition of freedom of movement; numerical	.0350	.041
DEP	Doubts about effect of ERP; numerical	.0442	.068
Daily mobility habits
LD	Dummy; 1 if licensed driver, 0 otherwise	.713	.453
PV	Dummy; 1 if commuter with car mode used, 0 otherwise	.240	.427
FV	Frequency of visiting CBDs (days/week)	2.227	1.422
MU	Dummy, 1 used private car, 0 otherwise	.504	.500
FC	Frequency of using car to enter city centers (days/week)	2.591	1.627

Table 8. Estimation results of SORM and GORM.

Variable	SORM		GORM
	Coeff.	t-value	Threshold 1		Threshold 2		Threshold 3
			Coeff.	t-value	Coeff.	t-value	Coeff.	t-value
Charge patterns
LR	−.452	−1.68	−.572	−1.33	−.405	−1.30	−.017	−.05
Latent constructs
ARP	−41.091	−2.32	−17.146	−.56	−43.129	−2.06	−50.468	−1.60
REP	41.534	2.36	14.585	.48	45.107	2.16	50.629	1.61
CDC	−6.571	−2.27	−8.852	−1.74	−2.976	−.87	−9.351	−1.74
APC	10.320	2.38	8.942	1.18	7.272	1.42	14.408	1.82
AFM	−2.967	−2.11	3.328	1.38	−5.941	−3.53	−3.982	−1.13
Daily mobility habits
LD	−.241	−3.47	−.162	−1.54	−.247	−2.97	−.533	−2.38
PV	−.180	−2.28	−.087	−.74	−.226	−2.36	−.060	−.30
FV	−.100	−4.56	−.028	−.78	−.123	−4.78	−.160	−2.64
MU	−.178	−3.08	−.505	−5.29	−.077	−1.14	.087	.65
FC	−.084	−3.75	−.056	−1.67	−.092	−3.43	−.116	−1.78
Thresholds
Cut 1		−2.179		−2.117
Cut 2		−.445				−.449
Cut 3		1.101						1.129
Summary of statistics
Sample size (n)		1,641						1,641
LL(0)		−2,274.91						−2,274.91
LL(β)		−1,642.15						−1,604.85
		.272						.279
AIC		1656.15						1640.85

Table 9. Summary of direct elasticity across outcomes.

Attributes	Marginal effects after GORM
	y = P(ac = 1) y = .0822		y = P(ac = 2) y = .556		y = P(ac = 3) y = .340		y = P(ac = 4) y = .0220		x (mean)
	dy/dx	S.D	dy/dx	S.D	dy/dx	S.D	dy/dx	S.D
Charge patterns
LV	−.076	.064	−.088	.120	−.159	.114	−.005	.031	2,484
Latent constructs
ARP	−2.544	4.606	−13.548	8.088	−13.476	7.565	−2.616	1.662	.048
REP	2.155	4.572	14.682	8.037	14.212	7.524	2.625	1.657	.047
CDC	−1.347	1.148	−1.359	1.982	−1.957	1.851	−.749	.424	.027
APC	1.337	.766	.236	1.321	.615	1.236	.486	.289	.035
AFM	−.506	.364	−2.732	.656	−2.019	.620	−.207	.183	.035
Daily mobility habits
LD	−.026	.018	−.065	.031	−.067	.029	−.023	.008	.713
PV	−.014	.019	−.069	.035	−.079	.033	−.003	.010	.239
FV	−.004	.005	−.042	.010	−.038	.010	−.008	.003	2.227
MU	−.077	.015	−.049	.026	−.033	.025	.005	.007	.504
FC	−.009	.005	−.026	.010	−.028	.010	−.006	.003	2.590

SITRAMP. (2004). The study on integrated transportation master plan for Jabodetabek. Jakarta: National Development Planning Agency of the Republic of Indonesia & JICA.

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