Influence of Social Constraints, Mobility Incentives, and Restrictions on Commuters’ Behavioral Intentions and Moral Obligation towards the Metro-Bus Service in Lahore

Abstract

This paper aims to identify commuters’ perceptions towards the metro-bus service system considering various social constraints, mobility incentives and restrictions, and personal norms. A questionnaire survey was designed, which consisted of the personal information of respondents, travel properties, and preferences with the metro-bus system. This survey was conducted in Lahore city, and a total of 333 samples were obtained. The findings of the Structural Equation Modeling (SEM) revealed that the social constraints in traveling, public transport incentives, and specific parking restrictions have a significant influence on commuters’ moral obligations to reduce traffic congestion, mitigate environmental menaces, and protect natural resources. The ANOVA and SEM analysis showed that significant differences exist among low-, middle-, and high-income commuters in terms of their behavioral intentions towards the metro-bus service. These findings implicate that specific incentives on the use of public transport modes and parking restrictions are useful in changing the behavioral intentions of travelers towards transit modes such as the metro-bus service.

Full text

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Citation: Javid, M.A.; Ali, N.;
Campisi, T.; Tesoriere, G.; Chaiyasarn,
K. Influence of Social Constraints,
Mobility Incentives, and Restrictions
on Commuters’ Behavioral Intentions
and Moral Obligation towards the
Metro-Bus Service in Lahore.
Sustainability 2022,14, 2654. https://
doi.org/10.3390/su14052654
Academic Editors: Renata
˙
Zochowska and Marianna Jacyna
Received: 29 January 2022
Accepted: 18 February 2022
Published: 24 February 2022
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sustainability
Article
Influence of Social Constraints, Mobility Incentives, and
Restrictions on Commuters’ Behavioral Intentions and Moral
Obligation towards the Metro-Bus Service in Lahore
Muhammad Ashraf Javid 1, Nazam Ali 2, Tiziana Campisi 3,* , Giovanni Tesoriere 3
and Krisada Chaiyasarn 4
1Department of Civil Engineering, NFC Institute of Engineering and Fertiliser Research, Faisalabad,
Punjab 38090, Pakistan; ma.javid@iefr.edu.pk
2Department of Civil Engineering, University of Management and Technology, Lahore 54770, Pakistan;
nazam.ali@umt.edu.pk
3
Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, 94100 Enna, Italy;
giovanni.tesoriere@unikore.it
4Thammasat Research Unit in Infrastructure Inspection and Monitoring, Repair and Strengthening (IIMRS),
Thammasat School of Engineering, Faculty of Engineering, Thammasat University Rangsit,
Klong Luang 12121, Thailand; ckrisada@engr.tu.ac.th
*Correspondence: tiziana.campisi@unikore.it
Abstract:
This paper aims to identify commuters’ perceptions towards the metro-bus service system
considering various social constraints, mobility incentives and restrictions, and personal norms. A
questionnaire survey was designed, which consisted of the personal information of respondents,
travel properties, and preferences with the metro-bus system. This survey was conducted in Lahore
city, and a total of 333 samples were obtained. The findings of the Structural Equation Modeling (SEM)
revealed that the social constraints in traveling, public transport incentives, and specific parking
restrictions have a significant influence on commuters’ moral obligations to reduce traffic congestion,
mitigate environmental menaces, and protect natural resources. The ANOVA and SEM analysis
showed that significant differences exist among low-, middle-, and high-income commuters in terms
of their behavioral intentions towards the metro-bus service. These findings implicate that specific
incentives on the use of public transport modes and parking restrictions are useful in changing the
behavioral intentions of travelers towards transit modes such as the metro-bus service.
Keywords: public transport; behavioral intentions; metro-bus; attitudes; mobility restrictions
1. Introduction
The unprecedented increase in the urban population and the vehicle ownership and its
excessive dependence have increased the travel demand on the urban road network. The
high trend of automobile dependency tends to increase traffic congestion and related social
and external costs. The public transport system is one of the essential entities of the urban
transport system, as the movement of people is mainly determined based on the quality
of the transport system. It is stated that choices on public transport systems determine
the city’s future regarding residence and workplace choice [
1
]. It is also believed that
individuals’ attitudes and intentions towards public transport policies are controlled and
influenced by the socio-demographics of the commuters, and it is a learning process that
evolves over time [
2
–
4
]. Many research studies have revealed that the behavioral intentions
to use public transport are mainly influenced by the perceived quality of the transport
service, environmental concerns, problem awareness, and sense of responsibility among
the commuters about negative outcomes of personalized vehicle use behavior pertinent to
the environment and socio-economic factors [5–9].
Sustainability 2022,14, 2654. https://doi.org/10.3390/su14052654 https://www.mdpi.com/journal/sustainability

Sustainability 2022,14, 2654 2 of 19
Different transit systems possess unique characteristics of service quality, e.g., the bus
rapid transit system differs from the conventional bus service in several ways, such as
the fact that it has an exclusive right of way and more frequent, comfortable, and reliable
service. It is reported that bus rapid transit systems or bus-bays have significant potential to
enhance the ridership of public transport. These bus lanes encourage mode switching from
private vehicles to transit modes, resulting in reduced travel time and urban traffic conges-
tion [
10
]. Researchers believe that people-based measures are more effective in assessing the
impacts of public transport in reducing traffic congestion [
11
]. The commuter ’s behavioral
intentions towards transit services are mostly affected by their perceptions about service
quality and satisfaction with the service [
12
]. Travel demand management (TDM) policies
are required to integrate and encourage more sustainable transport systems [
13
]. Mobility
incentives, such as low fare level, reliable service, comfortable ride, and disincentives for
car use, such as parking restrictions and other taxes, are important TDM policies to promote
sustainable travel behavior among commuters [
5
,
14
–
16
]. The situational, psychological,
personal, and social constraints also have a significant influence on travelers’ mode choice
behavior [
17
–
19
]. It is pertinent to mention that some of the additional factors also influ-
ence the transit ridership of public transport, and transit ridership can be predicted using
different modeling techniques, such as Artificial Neural Networking (ANN) [
20
], data from
smart cards using temporal motifs [
21
], and Modular Convolutional Neural Networks
(MCNNs) [22].
There is a range of factors influencing the public transport intentions of commuters.
The intentions and attitudes are especially governed by the local mobility restrictions
and incentive schemes and the service quality of competitive travel alternatives [
5
,
23
].
To encourage switching from car to mass-transit modes such as the metro-bus service, it
is required to identify suitable transport policies considering the local economic, social,
cultural, and transport infrastructure service conditions. It is also required to assess the
potential of suitable parking-management measures, such as parking fees and limited
parking spaces, to improve a model shift of transit modes. The findings of such perception-
based research studies can help concerned stakeholders and authorities in considering the
necessary intervention for the improvements in the public transport system. Therefore, this
study aims to explore commuters’ behavioral intentions and moral obligations towards the
metro-bus service in Lahore. Various social and personal factors, the restrictions of mobility
options, and the incentive systems about public transport are considered in this assessment.
The travelers’ moral obligation to use metro-bus for a reduction in environmental pollution
and preservation of natural resources are also part of this assessment. The data were
collected through the administration of a questionnaire survey that was conducted in
Lahore city. The collected data were analyzed using ANOVA testing, and a Structural
Equation Modeling approach was adopted for the investigation of correlations between
different latent variables. Comparison analysis between low-income, middle-income, and
high-income groups for behavioral intentions is also presented. The rest of the research
paper is written in the following manner. Section 2presents the relevant literature, and
study area characteristics are discussed in Section 3. In Section 4, the research methods
are elaborated. The results of the questionnaire survey and the findings are discussed in
Section 5. Finally, the main findings and conclusions of this research study are summarized.
2. Literature Review
The bus rapid transit (BRT) or metro-bus system (MBS) differs from other public
transport modes, such as conventional bus service, light-rail transit (LRT), and streetcars,
in infrastructure requirements and operational characteristics. Metro-bus systems usually
have an exclusive right of way or dedicated lanes of the highway for bus operation, and the
construction of infrastructure for a BRT or metro-bus system is less expensive as compared
to the rail infrastructure both in terms of time and money [
24
,
25
]. It provides a fast, reliable,
secure, frequent, safe, convenient, comfortable, and affordable service to users [
26
,
27
].
Metro-bus system provides better service than conventional bus service which is usually

Sustainability 2022,14, 2654 3 of 19
shared right of way with other traffic and takes more travel time. The metro-bus systems
are usually preferred in developing regions due to their low construction costs and they
do not depend upon the electric power supply, which is one of the important concerns
for countries with issue of power shortage [
28
]. LRT is an environmental friendly public
transport choice and it can offer high capacity at lower operating costs [
29
]. In comparison,
LRT is environmental friendly to BRT or metro-bus system, whereas BRT is a cost-effective
solution to the public transport needs [
29
]. The choice between different transit modes such
as BRT or LRT in a developing country also depends on people’s preferences and behavioral
intentions, city size, cost effectiveness, availability of land or right of way, environmental
concerns and social and political acceptance [
30
]. The prospects of a particular public
transport mode are needed to be evaluated in terms of user’s acceptance and behavioral
intentions for achieving required objectives.
The improvements in public transport modes play an imperative role in the travel
decision making of the local people. The transit service quality needs to meet the demand
of potential travelers. A study revealed that traveler’s age, gender, and marital status
have an indirect influence on commuter’s mode choice and the costs incurred due to
number of transfer points and distance to the nearest transit stations are significant factors
that hinder commuters from selecting the public transit system [
31
]. Fare reduction and
other associated incentives are effective in promoting the use of public transportation [
32
].
The driving age, car ownership, and income have the greatest impact on Pro-environment
Travel (PET) behavior. Additionally, perceived service quality of transit and Socio-economic
Characteristics (SEDs) of commuters play a significant role in the traveler’s decisions and
are strongly associated with PET behavior [
33
]. The female riders and those who belong to
low-household-income and live 5–10 km from the university have more favorable attitudes
towards public transport [34].
It is revealed that the comfort and security latent variables have a direct and significant
effect on the quality of public transit system [
35
]. The comfort experience of travelers plays
an essential role in determining the service satisfaction of the commuters, and women
are believed to be more sensitive as compared to males in their attribute. Crowding in
the public transport system has a direct and negative influence on how commuters rate
their travel experiences [
36
]. However, a study in Calgary showed that the people value
‘reliability and convenience’ over ride-comfort in public transport which implicates that
improvement in the train service connectivity, reducing transfer points, and providing
exclusive rights-of-way for public transport services would increase transit ridership [
37
]. It
is also believed that an increase in the car travel cost and improvement in the service quality
of public transport are both helpful in switching car users to public transport [
38
]. The
comfort, travel cost, and reliability play a significant role in the willingness of commuters to
travel by public transport [
38
]. Researchers believed that the perceived value of a trip using
a the transit service is one of the most important factors of behavioral intentions [
39
]. Other
studies have shown that access to important destinations by transit modes is also significant
for the preferences of commuters with the transit system [
3
,
40
,
41
]. The land-use patterns
and travel speeds are significant predictors of the travel demand and high use of the public
transport systems which results in the reduction of energy use and emissions [42].
It is found that the passengers of a bus-way are influenced by their preferential (riding
experience), moral (pro-environmental concerns), and travel constraints considerations [
13
].
The traveler’s problem experience and public perceived perceptions about service quality
put a strong impact on peoples’ behavioral intentions towards transit modes [
43
]. It has
been reported that the Descriptive Norm (DN), the relationships between the intentions and
the Perceived Behavioral Control (PBC) significantly determine the student’s experiences
about bus ridership [
44
]. Researchers have argued that to make a model shift to public
transport, transport policies should focus on individual’s environmental-related beliefs,
norms, and situational constraints [
45
]. It is believed that mobility restrictions on the use of
a private car are mandatory to increase the travel demand of public transport modes [
46
].

Sustainability 2022,14, 2654 4 of 19
Parking management measures such as limited and paid parking are always effective in
making behavioral changes among travelers especially in urban areas [14,47,48].
The behavioral intentions to use BRT service are determined by the perceived social
influence or subjective norms and private car users have less intentions to use BRT [
49
,
50
].
Other researchers have argued that attitudes toward public transport are dominant in
determining behavioral intentions in comparison to their social influence or subjective
norms and perceived behavioral control [
51
]. The travel cost also plays significant role in
the mode choice behaviors. A study using a stated choice experiment showed that the travel
time, fare and comfort are prominent factors in determining BRT choice in Dar es Salaam,
Tanzania [
52
]. The service quality attributes, individual’s attitudes and environmental
impacts are found to have positive influence on the behavioral intentions of commuters to
use the public transport modes [
53
]. The social, religious and cultural context of the country
tend to influence in shaping the female mobility choices, and age, household income,
and marital status significantly decrease the female mobility choices in the developing
regions [
54
]. Researchers have identified the major challenges of the women mobility with
BRT service in Lahore which includes harassment at stations and in buses, the availability
of limited facilities, especially for the elderly people, the limited dedicated space for the
females in the buses and the inconvenient behavior of passengers at the ticketing booths
during rush hours [55]. It has been found that commuter’s perceptions about BRT service
quality vary across different demographics aspects, such as gender, travel time, profession
type, education, and purpose of trip. It is also reported that commuter’s perceptions differ
across different regions [56].
The above-mentioned literature reveals that several factors including attributes of the
service quality, situational constraints, mobility restrictions, incentives, and personal norms
influence the individual’s behavioral intentions to use the public transport modes including
BRT or metro-bus services. However, the significant influencing factors may have different
policy implications concerning to a specific region because the social, cultural values, local
regulations, and the public transport characteristics vary among different regions. The
transportation improvement policies derived based on the findings of a particular case
study may not produce the desired results for another region as each region or city has its
own unique characteristics. Under these circumstances, it becomes extremely important to
evaluate people’s perceptions at the local or regional level. There is lack of knowledge es-
pecially in developing regions on evaluating the impacts of parking management measures
in changing the behavioral intentions towards the metro-bus service. It is also required
to understand the role of pro-social norms and social constraints in understanding the
behavioral intentions of commuters towards the metro-bus system. In addition, some of the
incentives attributes of the metro-bus were also added in this research. It was hypothesized
that the commuter’s social constraints and parking restrictions influence their behavioral
intentions with some incentives on using the metro-bus over a private car. Social constraints
and parking restrictions may have direct effects on personal norms or moral obligations
of commuters to use the metro-bus for the reduction of air pollution, traffic congestion,
and preservation of natural resources. The metro-bus intentions with incentives have a
direct correlation with the personal norms of the commuters. It was also hypothesized that
the personal and trip characteristics may have significant correlations with the metro-bus
behavioral intentions, the personal norms and commuters’ behavioral intentions may vary
across different income groups. These entire hypotheses were tested for significance using
ANOVA and SEM analyses.
3. Characteristics of the Study Area
Lahore is the 2nd biggest city of Pakistan and the capital of the most populace province,
Punjab, with an estimated population of more than 11 million and the area of the city is
believed to be extended about 1792 km
2
[
57
]. It has many medical, educational, and recre-
ational facilities and industrial zones. It also provides a lot of employment opportunities
for a great portion of the population from the surrounding areas. Due to the presence of

Sustainability 2022,14, 2654 5 of 19
these facilities and industrial zones, many people travel from suburban and rural areas
which generate high travel demand. In the densely populated regions, the demand for
public transport is more as compared to the outskirt areas. The unprecedented growth
in the mobility patterns have taken place in the few years because of the construction of
underpasses, flyovers, and, most importantly, because of the introduction of metro-bus
and orange line train services in the transport infrastructure of the city. Currently, the
public transport system in the city consists of para-transit services, metro-bus system with
a length of 28 km and orange-line metro train route of 27.1 km length. However, it is
pertinent to mention that the conventional public transport system is still dominant in the
city because of its easy accessibility, cheaper costs, and better coverage. The capacity of
the conventional transport modes ranges from 4–20 passengers which can be transported
using these para-transit services. These modes also serve as feeder routes to the metro-bus
service. All of the combined public transport modes constitute around 20% of the total
modal share of Lahore city [
58
]. The share of the private modes in the model share is very
high that causes an increase in traffic congestions on the road network.
Metro bus service was started in February 2013 having 28 km long route with 29 bus
stations between Gajumata and Shahadra. This bus route was selected along one of the
major arteries of the city. This route connects many important destinations, including
commercial areas, business centers, and official buildings. Route map of the metro bus
service with station details, typical bus-stop, and articulated bus route are presented in
Figure 1[
59
]. Around 8 km section of the route is elevated. The metro-bus route with
the help of feeder routes provides spatial coverage to wider area of the city. It passes
through some of the main commercial markets and connects them with densely developed
residential areas. The high-density developments near some sections of the metro-bus
route are also helpful in generating more metro trips as it can be accessed by walking.
The park-and-ride facilities are also provided at some of the stations for the bicyclists and
motorcyclists. They can securely park their vehicles near stations and take a ride of the
metro-bus. The metro-bus uses e-ticketing and smart card methods for the fare collection.
Real-time information is also provided to the passengers during their traveling related to
the bus stations or stops and estimated time to reach the next station.
Sustainability 2022, 14, x FOR PEER REVIEW 5 of 21
recreational facilities and industrial zones. It also provides a lot of employment opportu-
nities for a great portion of the population from the surrounding areas. Due to the pres-
ence of these facilities and industrial zones, many people travel from suburban and rural
areas which generate high travel demand. In the densely populated regions, the demand
for public transport is more as compared to the outskirt areas. The unprecedented growth
in the mobility patterns have taken place in the few years because of the construction of
underpasses, flyovers, and, most importantly, because of the introduction of metro-bus
and orange line train services in the transport infrastructure of the city. Currently, the
public transport system in the city consists of para-transit services, metro-bus system with
a length of 28 km and orange-line metro train route of 27.1 km length. However, it is per-
tinent to mention that the conventional public transport system is still dominant in the
city because of its easy accessibility, cheaper costs, and better coverage. The capacity of
the conventional transport modes ranges from 4–20 passengers which can be transported
using these para-transit services. These modes also serve as feeder routes to the metro-bus
service. All of the combined public transport modes constitute around 20% of the total
modal share of Lahore city [58]. The share of the private modes in the model share is very
high that causes an increase in traffic congestions on the road network.
Metro bus service was started in February 2013 having 28 km long route with 29 bus
stations between Gajumata and Shahadra. This bus route was selected along one of the
major arteries of the city. This route connects many important destinations, including
commercial areas, business centers, and official buildings. Route map of the metro bus
service with station details, typical bus-stop, and articulated bus route are presented in
Figure 1 [59]. Around 8 km section of the route is elevated. The metro-bus route with the
help of feeder routes provides spatial coverage to wider area of the city. It passes through
some of the main commercial markets and connects them with densely developed resi-
dential areas. The high-density developments near some sections of the metro-bus route
are also helpful in generating more metro trips as it can be accessed by walking. The park-
and-ride facilities are also provided at some of the stations for the bicyclists and motorcy-
clists. They can securely park their vehicles near stations and take a ride of the metro-bus.
The metro-bus uses e-ticketing and smart card methods for the fare collection. Real-time
information is also provided to the passengers during their traveling related to the bus
stations or stops and estimated time to reach the next station.
(a)
(b) (c) (d)
Figure 1.
Metro bus route, a typical articulated bus, and station. (
a
) Metro-bus route map with station
details. (
b
) A typical articulated bus. (
c
) A typical at-grade station. (
d
) A ticket machine. (Source:
Punjab Mass-transit Authority. Available online: https://pma.punjab.gov.pk/lmbsrm (accessed on 3
January 2022)).

Sustainability 2022,14, 2654 6 of 19
The metro-bus service usually operates at varying headways of around 2.25 to 3 min
during the peak-hours and its operation starts at 06:15 a.m. in the morning and ends
around 10:00 p.m. at night [
59
]. The flat fare of 30 PKR is charged for one ride regardless
of the origin and destination on the route. A metro-bus guide with video is also available
at the website of the Punjab Mass-transit Authority (PMA). This guide includes a video
demonstration related to the process of obtaining a ticket and charging smart cards. There
are separate compartments inside the bus for the male and female travelers which are
separated in order to ensure the security, safety, and maintain the necessary privacy of the
female commuters [
3
,
59
,
60
]. The stations are equipped with escalators to make convenient
access. Various feeder modes are connecting the users to access the metro-bus, such as the
conventional bus system, minibus, auto and Qingqi rickshaw and minivans. Some newer
feeder routes are also started by the government to facilitate the people who live far from
the metro route and want to use this service. Metro bus route can carry almost 112,000
people per day [59].
4. Methods
4.1. Questionnaire Design and Survey
A questionnaire was designed in this study comprising the traveler’s socio-economic
demographics (SEDs) and behavioral intentions towards the metro-bus service considering
various constraints, metro-bus incentives, and disincentives on the use of private car. The
respondent’s age, gender, marital status, vehicle ownership, occupation, education, and
personal income were asked in the first part of the questionnaire. The second part of the
questionnaire consisted of the travel characteristics of the respondents, such as frequent
travel mode, trip frequency, travel time, and cost of frequent travel mode, and trip distance
of a commuting trip. The third part of the questionnaire consisted of various statements
related to commuter’s intentions to use metro-bus service considering various situational
factors, mobility constraints, incentives, and moral obligations. The main hypothesis
of social constrained statements included traveling alone, travelling with friends, and
other family members. It was assumed that travelling alone and with others may result
in different behavioral intentions towards the public transport as coupling and social
constraints or social ties tend to influence the mode choice behavior of the people [
49
,
61
].
Economic and other incentives were included in designing the statements to ask the
respondents’ intentions towards metro-bus. These incentives included reduced travel
cost and time with metro-bus service in comparison to a private car. It was assumed that
reduced travel time and cost with the metro-bus service may have significant impact on
altering user’s behavioral intentions. These incentives will serve as pull measures to attract
people towards the metro-bus. Additionally, disincentives on the use of a private car were
included such as parking restrictions and charges. These disincentive schemes will suffice
the purpose as push measures in shifting the people from private car to the public transport
modes. Respondent’s moral obligations were also asked to use the metro-bus service for
the reduction of the traffic congestion, air pollution and to preserve the natural resources.
In this survey, the users who use different modes for their daily commute were also
included. The purpose of surveying the users of various modes is to know their intentions
with the metro service under various scenarios. A convenience-based random sampling
strategy was adopted in the selection of the potential respondents. This survey was
conducted alongside the metro-bus route at selected locations where it was possible to find
the target population. It was assured that the target respondents should be aware about
metro-bus route and should have been either living or working near the metro-bus route
and stations. The sample size was determined considering the minimum requirements of
sample size for use in the Structural Equation Modeling (SEM) [
62
–
65
]. All the respondents
were interviewed at their convenience. At the start of the survey, the respondents were
instructed regarding the contents and objectives of the survey. A total of 333 usable samples
were obtained in this survey.

Sustainability 2022,14, 2654 7 of 19
4.2. Analysis Methods
The collected data were analyzed using the multivariate statistical analysis methods.
Initially, the Principal Component Analysis (PCA) was conducted on commuter’s per-
ceptions of designed statements related to the metro-bus service behavioral intentions.
PCA is an exploratory analysis approach that provides the required factors or compo-
nents. Cronbach’s alpha values were estimated to check the reliability of the collected data
and extracted components. The extracted components or factors were combined to con-
struct a structural model using the Structural Equation Modeling (SEM) technique. Many
studies have used this multi-variant analysis technique in analyzing the travel behavior
patterns [
66
,
67
]. A structural model is a combination of several measurement models. The
SPSS AMOS software was used to develop the structural models. The AMOS analysis uses
a confirmatory approach to construct the structure and test several hypotheses at the same
time. This technique also elicits the direct and indirect effects between the variables of a
structural model. In this study, it was hypothesized that the commuter’s intentions with the
metro-bus service under various constraints, mobility restrictions, and incentives influence
their moral obligations or personal norms. The structural model was extended by including
observed variables concerning the socio-economic and personal features of the travelers.
The adequacy of the structural models was examined using a significance level of measure-
ment, structural equations, and comparing indices of the goodness of fit parameters with
their permissible or recommended values in the literature. The selected goodness of fit
parameters included the ratio of Chi-square to the Degree of Freedom (
χ2
/DF), Goodness
of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Comparative Fit Index (CFI),
and Root Mean Square Error of Approximation (RMSEA). The recommended value of
χ2
/DF is2–5, CFI, GFI, and AGFI is more than 0.9, and RMSEA is supposed to be less than
0.08 [68,69].
5. Results and Discussion
5.1. Descriptive Statistics of Sample
The descriptive statistics of the respondent’s SEDs are shown in Table 1. The share of
the male respondents is more than the female respondents. Most of the respondents belong
to the age group of 21–30 years. More than 60% of the respondents own a car and more
than 50% own a motorcycle. Around 45% of the respondents possess a driving license.
Results show that private cars and motorcycles have a major share in the study model split
which is consistent with their actual share among the motorized modes in Lahore city [
58
].
Most of the respondents work in private and civil organizations.
Table 1. SEDs of the respondents.
Characteristics Distribution (%)
Gender Male (67.6), female (32.4)
Marital status Single (65.8), married (34.2)
Age (years) Under 20 (4.8), 21–30 (72.7), 31–40 (12.6), 41–50 (8.1), above 50 (1.8)
Household size 3 or less than 3 (11.7), 4–5 (36.1), 5–6 (36.0), more than 6 (16.2)
Profession Student (23), civil employees (42), private employees (28), others (7)
Personal income (PKR)
<15,000 (27), 15,000–25,000 (12), 26,000–40,000 (28), 41,000–60,000 (19),
more than 60,000 (14)
Frequent travel mode Walking/bicycle (13), private car (29), motorcycle (32), public
transport (22), auto-rickshaw/taxi (4)
Trip frequency 5–7 days a week (85.6), 3–4 days a week (9.0), 1–2 days a week (5.4)
Lives in a joint family Yes (49.2), No (50.8)
Have a driving license Yes (44.7), No (55.3)
Motorcycle ownership Yes (49.2), No (50.8)
Car ownership Yes (61.3), No (38.7)

Sustainability 2022,14, 2654 8 of 19
5.2. Distribution of Responses on the Metro-Bus Intentions
The distribution of the respondents’ responses on attitudes and intentions towards
the metro-bus service is shown in Figure 2. It shows that the commuter’s intentions to
use the metro-bus service in situational and social constraints are quite low, especially
when they are traveling with their family members. It means that they would prefer
private modes of transport when going out with the family members. The selected parking
restrictions such as a parking fee of Rs. 100 and limited parking spaces near the metro-bus
route have shown a significant impact on the commuter’s behavioral intentions to use the
metro-bus service. It is evident that the implementation of mentioned parking management
measures would have significant impact on changing traveler’s behavioral intentions. High
parking fees and limited parking spaces would discourage the use of private transport and
encourage use of the metro-bus service. The incentives of the direct access by the metro-bus
to the important destinations, service reliability, and the travel cost and time reduction
have important considerations in changing the behavioral intentions of the travelers. It is
prevalent that the people may prefer the metro-bus over private car if it provides better
access or has better spatial coverage, the travel cost and time are lower than the use of car.
The respondents have shown high moral obligations to use the metro-bus service for the
community and economic benefits which depict their pro-social behavior. The presence of
such pro-social norms is usually helpful in shaping sustainable travel behaviors among the
travelers [5,70,71].
Sustainability 2022, 14, x FOR PEER REVIEW 9 of 21
Figure 2. Frequency distribution of the respondent’s intentions towards metro-bus.
5.3. Average Responses on the Metro-Bus Intentions across Different Income Groups
The sample was divided into three categories considering the income group of re-
spondents, i.e., low-income (≥20,000 PKR), middle-income (21,000–40,000 PKR), and high-
income (more than 40,000 PKR). The sample sizes of low-income, middle-income, and
high-income are 112, 112, and 109, respectively. Average responses were estimated about
the metro-bus behavioral intentions and are presented in Figure 3. The contours in the
diagram represent the statement scale from 1 to 5, where 1 is never and 5 is always. The
radar diagram in Figure 3 shows that there is a difference in the perceptions of these in-
come groups. The average responses are almost the same across three groups when they
need to travel with their elder family members. It is clear from the figure that the low-
income group places high intentions for the metro-bus service considering various social
constraints, mobility restrictions, and incentives. The high-income people have shown low
intentions towards buses under given circumstances. Their intentions are only more when
there are some heavy restrictions on the car use such as when the entry of a car is restricted
in the public transport service area.
123
206
113
229
48
40
48
24
33
53
60
86
40
67
34
27
29
46
40
60
27
61
58
27
35
33
37
52
47
50
50
30
23
25
60
32
72
35
88
83
89
72
79
63
53
61
57
63
76
77
66
57
33
45
26
75
84
86
85
76
77
75
61
78
73
97
93
94
47
22
43
16
61
68
83
117
112
103
93
78
108
80
96
113
119
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Travelling alone to office/school/university
Travelling to office/school/university with family members
Travelling to office/school/university with friends
Travelling with elder family members
When parking is limited at the destination place
When parking is very far from your destination place
When the parking fee for car is about 100 PKR at the destination
When entry of car is restricted in metro-bus service area
When you can reach many important destinations directly by metro-bus
When travel cost by metro-bus is half of car
When travel time by metro-bus is 10 minutes less than a car travel time
When seat is assured in metro-bus with same travel cost as a car
When metro-bus is more reliable mode than private car
When seat is assured in metro-bus with same travel time as car
When you feel moral obligation to do not use car for reduction in
congestion
When you feel moral obligation to protect environment from air
pollution
When you feel moral obligation to preserve natural resources e.g.
oil, gas
Never Rarely Sometimes Often Always
Figure 2. Frequency distribution of the respondent’s intentions towards metro-bus.

Sustainability 2022,14, 2654 9 of 19
5.3. Average Responses on the Metro-Bus Intentions across Different Income Groups
The sample was divided into three categories considering the income group of re-
spondents, i.e., low-income (
≥
20,000 PKR), middle-income (21,000–40,000 PKR), and high-
income (more than 40,000 PKR). The sample sizes of low-income, middle-income, and
high-income are 112, 112, and 109, respectively. Average responses were estimated about
the metro-bus behavioral intentions and are presented in Figure 3. The contours in the
diagram represent the statement scale from 1 to 5, where 1 is never and 5 is always. The
radar diagram in Figure 3shows that there is a difference in the perceptions of these income
groups. The average responses are almost the same across three groups when they need to
travel with their elder family members. It is clear from the figure that the low-income group
places high intentions for the metro-bus service considering various social constraints,
mobility restrictions, and incentives. The high-income people have shown low intentions
towards buses under given circumstances. Their intentions are only more when there are
some heavy restrictions on the car use such as when the entry of a car is restricted in the
public transport service area.
Sustainability 2022, 14, x FOR PEER REVIEW 10 of 21
Figure 3. Average responses with ANOVA results for three income groups.
One-way ANOVA analysis was conducted on the behavioral intentions across the
three groups to determine the statistical significance of their differences in responses. The
F-statistics and significance values are shown in Figure 3. This analysis showed that the
responses of low-, middle-, and high-income respondents are not statistically different
when they are traveling with their family members and friends, whereas the responses
are statistically significantly different when they are traveling alone. Similarly, the re-
sponses for other behavioral intentions towards the metro-bus service are statistically sig-
nificant and different across the three income groups of the respondents. These results
depict that the behavioral intentions of low-income, middle-income, and high-income re-
spondents differ significantly when certain mobility incentives and restrictions are im-
posed.
5.4. Exploratory Factor Analysis
The Principal Component Analysis technique was employed for the extraction of ex-
planatory factor analysis on the commuter’s perceptions. The component rotation was
done using the varimax rotation method. A factor loadings value of 0.5 was used for the
extraction purposes. This component analysis resulted in four components for an eigen-
value greater than 1.0 as shown in Table 2. The estimates of KMO and Bartlett’s tests show
that the sample size is adequate for an explanatory factor analysis as the value of KMO is
more than 0.7 and the test is highly significant [72,73]. These components were named
based on the nature of the questions asked in the questionnaire. These components are (1)
Metro-Bus Incentives (MBI), (2) Social Constraints (SC), (3) Personal Norms (PN), and (4)
Figure 3. Average responses with ANOVA results for three income groups.
One-way ANOVA analysis was conducted on the behavioral intentions across the
three groups to determine the statistical significance of their differences in responses. The
F-statistics and significance values are shown in Figure 3. This analysis showed that the
responses of low-, middle-, and high-income respondents are not statistically different
when they are traveling with their family members and friends, whereas the responses are
statistically significantly different when they are traveling alone. Similarly, the responses

Sustainability 2022,14, 2654 10 of 19
for other behavioral intentions towards the metro-bus service are statistically significant
and different across the three income groups of the respondents. These results depict that
the behavioral intentions of low-income, middle-income, and high-income respondents
differ significantly when certain mobility incentives and restrictions are imposed.
5.4. Exploratory Factor Analysis
The Principal Component Analysis technique was employed for the extraction of
explanatory factor analysis on the commuter’s perceptions. The component rotation was
done using the varimax rotation method. A factor loadings value of 0.5 was used for
the extraction purposes. This component analysis resulted in four components for an
eigenvalue greater than 1.0 as shown in Table 2. The estimates of KMO and Bartlett’s tests
show that the sample size is adequate for an explanatory factor analysis as the value of
KMO is more than 0.7 and the test is highly significant [
72
,
73
]. These components were
named based on the nature of the questions asked in the questionnaire. These components
are (1) Metro-Bus Incentives (MBI), (2) Social Constraints (SC), (3) Personal Norms (PN),
and (4) Parking Restrictions (PR). The % of variance explained by all these four factors is
more than 60% of the total variance which is within an acceptable range. Additionally, the
values of the estimated Cronbach’s alpha confirm the acceptable level of reliability because
the value is more than 0.7 which validates the internal consistency among respondents
in the evaluation of the indicators or observed variables [
72
,
73
]. The first factors of MBI
included indicators concerning hypothetical metro-bus incentives over private car such
as more reliable and cheap service, less travel time with metro-bus service, direct access
to many important destinations by metro-bus, and seat assurance in the bus service. This
factor shows that the commuters placed a high score on the reliability, cost and travel time
saving, and direct access attributes. The second factor of SC shows that the situational
and social constraints have a significant influence on the commuter’s intentions to use the
metro-bus service. Commuters would like to use their personalized vehicles when they are
traveling with their family members. The results of the PN depict that the travelers have a
high moral obligation to use the metro-bus service for the reduction of traffic congestions,
air pollution, and the preservation of the natural resources. These pro-social norms would
help to promote the use of the public transportation modes such as metro-bus service.
The last factor of PR shows that the selected parking restrictions such as restricted and far
parking and parking fee have a significant influence on changing the commuter’s intentions
towards the metro-bus service.
5.5. Structural Equation Modeling of Metro-Bus Intentions
The SEM model was developed using PCA technique in order to understand the
relationships of different latent variables. It was hypothesized that the situational and
social constraints and parking restrictions may have a significant direct influence on the
metro-bus intentions (MBI) under various incentives and personal norms (PN). A direct
structural relationship was assumed between MBI and PN. It was also hypothesized that
the passenger’s SEDs and trip characteristics may impact their norms. Therefore, the
observed variables of the SED sand trip characteristics are clearly defined and incorporated
in the model. However, these variables are coded for the convenience of analysis as
binary variables (i.e., 1, 0). It is pertinent to mention that the variables which are statistically
significant are only presented in Figure 4. The defined variables incorporated are profession
(1 if the profession belongs to the group of private employees, otherwise is 0; 1 if the
profession belongs to the group of civil employees, otherwise is 0), marital status (1 if
respondents are married, otherwise is 0), motorcycle ownership (yes: 1, no: 0), and have a
driving license (yes: 1, no: 0). The variable of the trip distance was included in km.

Sustainability 2022,14, 2654 11 of 19
Table 2. Results of rotated principal component analysis (PCA).
Observed Variables Mean
Components
Metro-Bus
Incentives (MBI) Social Constraints
(SC)
Personal Norms
(PN)
Parking
Restrictions (PR)
When metro-bus is more reliable mode than a
private car. (MBI-1) 3.492 0.795
When travel cost by metro-bus is half of the
car. (MBI-2) 3.420 0.784
When travel time by metro-bus is 10 min less
than a car travel time. (MBI-3) 3.267 0.767
When you can reach many important
destinations directly by metro-bus. (MBI-4) 3.604 0.718
When a seat is assured in metro-bus with the
same travel time as a car. (MBI-5) 3.147 0.716
When entry of the car is restricted in the
metro-bus service area. (MBI-6) 3.709 0.681
When a seat is assured in metro-bus with the
same travel cost as a car. (MBI-7) 2.994 0.675
Traveling to office/school/university with
family members. (SC-1) 1.874 0.889
Traveling with elder family members. (SC-2) 1.718 0.867
Traveling to office/school/university with
friends. (SC-3) 2.535 0.642
Traveling alone to office/school/university. (SC-4) 2.577 0.619
When you feel a moral obligation to protect the
environment from air pollution. (PN-1) 3.727 0.910
When you feel a moral obligation to preserve
natural resources, e.g., oil, gas. (PN-2) 3.748 0.904
When you feel a moral obligation to do not use a
car for the reduction in congestion. (PN-3) 3.574 0.551
When parking is limited at the destination
place. (PR-1) 3.120 0.817
When parking is very far from your destination
place. (PR-2) 3.246 0.759
When the parking fee for a car is about 100 PKR
at the destination. (PR-3) 3.387 0.511
% of variance explained 27.546 15.486 13.188 12.101
Cronbach’s alpha 0.898 0.808 0.833 0.765
KMO and Bartlett’s test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. 0.896
Bartlett’s Test of Sphericity Approximate Chi-Square 3094.237
Degree of freedom 136
Significance 0.000
The significance of all of the measurement equations was checked at a 1% level of
significance and confirmed their association with their corresponding latent variables
(factors) as shown in Figure 4. PR and SC have a positive and significant association
with each other. The structural coefficient of SC with MBI is insignificant. The structural
relationship of PR with MBI is positive and significant at a 1% level of significance. This
positive coefficient depicts that the respondent’s behavioral intentions under parking
restrictions have a positive association with the metro-bus incentives in comparison to the
car. It is argued that parking restrictions in combination with metro-bus incentives would
be handy in promoting the use of metro-bus service among the existing and potential
commuters. The SC and PR explain almost 59% of the variance in the MBI.
The structural relationship of SC with PN is insignificant. The PR has a positive and
significant structural construct with PN. It shows that the respondents who have positive
intentions to use the metro-bus with parking restrictions also feel a moral obligation to
reduce the use of private cars, protect the environment from air pollution, and preserve
the natural resources. The structural coefficient of MBI with PN is positive and significant
at a 1% level of significance. This relationship depicts that the respondent’s positive
intentions with the metro-bus incentives over a private car have a significant influence
in developing the pro-social norms among the commuters. These positive norms can be
handy in the long run to reduce the use of private vehicles and promote the use of mass
transit modes [5,13,71].

Sustainability 2022,14, 2654 12 of 19
Sustainability 2022, 14, x FOR PEER REVIEW 12 of 21
5.5. Structural Equation Modeling of Metro-Bus Intentions
The SEM model was developed using PCA technique in order to understand the re-
lationships of different latent variables. It was hypothesized that the situational and social
constraints and parking restrictions may have a significant direct influence on the metro-
bus intentions (MBI) under various incentives and personal norms (PN). A direct struc-
tural relationship was assumed between MBI and PN. It was also hypothesized that the
passenger’s SEDs and trip characteristics may impact their norms. Therefore, the observed
variables of the SED sand trip characteristics are clearly defined and incorporated in the
model. However, these variables are coded for the convenience of analysis as binary var-
iables (i.e., 1, 0). It is pertinent to mention that the variables which are statistically signifi-
cant are only presented in Figure 4. The defined variables incorporated are profession (1
if the profession belongs to the group of private employees, otherwise is 0; 1 if the profes-
sion belongs to the group of civil employees, otherwise is 0), marital status (1 if respond-
ents are married, otherwise is 0), motorcycle ownership (yes: 1, no: 0), and have a driving
license (yes: 1, no: 0). The variable of the trip distance was included in km.
CMIN/DF = 3.548, GFI =0.816, AGFI =0.774, CFI = 0.826, RMSEA = 0.088.
Figure 4. A structure of commuter’s intentions towards metro-bus service.
The significance of all of the measurement equations was checked at a 1% level of
significance and confirmed their association with their corresponding latent variables
SC
PR
SC-1
SC-2
SC-3
SC-4
PR-1
PR-2
PR-3
PN
PR-1
PR-2
PR-3
MBI
MBI-1
MBI-2
MBI-3
MBI-4
MBI-5
MBI-6
MBI-7
Private
employees
Own a
motorcycle
Married
status
Have a driving
license
Civil
Employees
Trip
distance
0.85***
0.78***
0.63***
0.63***
0.45***
0.78***
0.73***
0.68***
0.90***
0.88***
0.63***
0.83***
0.82***
0.74***
0.65***
0.68***
0.69***
0.79***
−0.04
0.05
0.10**
0.15***
−0.13***
0.44***
0.75***
0.18**
−0.12**
0.09*
−0.12**
*** Significant at 1% (p < 0.01)
** Significant at 5% (p < 0.05)
* Significant at 5% (p < 0.10)
R2 = 0.59
R2 = 0.38
Figure 4. A structure of commuter’s intentions towards metro-bus service.
The commuter’s profession such as civil and private employees has a positive and
significant association with the latent variable of PN. It shows that the employees feel a
moral obligation and possess pro-social travel behavior. These pro-social behavioral inten-
tions among employees can be useful in promoting the use of the public transport modes.
The respondents who are married and possess a driving license formed negative structural
coefficients with PN. These coefficients show that the commuters with a driving license
and family members have low intentions to reduce the use of a private car for the reduction
of traffic congestion, air pollution, and preservation of the natural resources. Other studies
have also shown that the traveler’s characteristics, such as profession, marital status, and
vehicle ownership, have a significant influence on the behavioral
intentions [18,45,74].
It is
found that an increase in the trip distance has a negative impact on the moral obligations of
the people as the structural coefficient is negative. The respondents who own a motorcycle
have a positive association with the formation of moral obligations among them. The MBI,
SC, and PR and significant personal and travel characteristics explain almost 38% of the
variance in the PN. The values of all the threshold indices are within the acceptable range
which confirmed the validity of the proposed SEM model in explaining the commuter’s
behavioral intentions towards metro-bus.

Sustainability 2022,14, 2654 13 of 19
5.6. Structural Models of Low-, Medium-, and High-Income Groups
The SEM analysis was performed to draw a comparison between low-income, middle-
income, and high-income groups. The sample sizes for low, middle, and high-income
people are 112, 112, and 109, respectively. The standardized estimates of the structural
equations and measurement equations are presented in Table 3and Figure 5, respectively.
All the measurement equations of the three groups were positive and significant at a
1% level of significance. Some differences have existed in the standardized estimates or
regression weights among the three groups as shown in Table 3.
Table 3. Standardized estimates of measurement equations of the three income groups.
Measurement Equation Low-Income Middle-Income High-Income
PN-3 <— PN 0.736 0.459 0.646
PN-2 <— PN 0.904 0.854 0.882
PN-1 <— PN 0.837 0.952 0.921
SC-2 <— SC 0.689 0.866 0.796
SC-4 <— SC 0.617 0.572 0.715
SC-1 <— SC 0.797 0.874 0.859
SC-3 <— SC 0.635 0.517 0.748
PR-3 <— PR 0.703 0.495 0.749
PR-1 <— PR 0.763 0.734 0.831
PR-2 <— PR 0.641 0.798 0.697
MBI-4 <— MBI 0.741 0.706 0.726
MBI-2 <— MBI 0.846 0.847 0.764
MBI-7 <— MBI 0.628 0.671 0.713
MBI-3 <— MBI 0.725 0.812 0.798
MBI-1 <— MBI 0.763 0.897 0.789
MBI-6 <— MBI 0.644 0.647 0.717
MBI-5 <— MBI 0.703 0.651 0.644
Note: <— shows the measurement equation or relationship between observed variable and latent variable,
PN: personal norm, SC: social constraints, PR: parking restrictions, MBI: Metro-bus incentives.
The structural estimates in Figure 5a of the low-income group show that the PR has
positive and significant coefficients with MBI and PN which depict that the behavioral
intentions of low-income people under parking restrictions have a positive association
with their moral obligations and intentions towards the metro-bus service with given
incentives. SC and PR have a positive association with each other. In middle-income models
in Figure 5b, the PR has only a significant relationship with MBI whereas the structural
coefficient with PN was insignificant. Figure 5c shows that the PR has a significant structural
construct both with MBI and PN. The structural estimate of private employees with PN is
the only significant relationship in the low-income model. In the middle-income model,
the variables of marital status, motorcycle ownership, and trip distance have significant
structural relationships with the PN. In the high-income model, all the defined variables of
the personal and travel characteristics (same as the base model in Figure 4) have significant
structural relationships with the PN. The impacts of motorcycle ownership, marital status,
trip distance, profession, and driving license variables on PN are the same as of the base
model in Figure 4. The income level and profession of commuters and trip distance have a
significant influence on traveler’s behavioral intentions [75–77].
The commuter’s behavioral intentions with the metro-bus incentives have a positive
construct with their moral obligations in all three models. It predicts that the pro-social
norms of the commuters are helpful to reduce the traffic congestion and air pollution in the
city and preserve the natural resources. The overall comparison of the measurement and
structural equations with their significance level and indices of the goodness-of-fit parame-
ters show that the structural model of high-income groups has a better representation of the
base model in predicting the behavioral intentions and personal norms of the commuters.

Sustainability 2022,14, 2654 14 of 19
Sustainability 2022, 14, x FOR PEER REVIEW 14 of 21
Figure 5. Standardized estimates of three income groups’ structural models.
Table 3. Standardized estimates of measurement equations of the three income groups.
Measurement Equation Low-Income Middle-Income High-Income
PN-3 <--- PN 0.736 0.459 0.646
PN-2 <--- PN 0.904 0.854 0.882
PN-1 <--- PN 0.837 0.952 0.921
SC-2 <--- SC 0.689 0.866 0.796
SC-4 <--- SC 0.617 0.572 0.715
SC-1 <--- SC 0.797 0.874 0.859
SC-3 <--- SC 0.635 0.517 0.748
*** Significant at 1% (p < 0.01), ** Significant at 5% (p < 0.05), * Significant at 5% (p < 0.10)
(c) Structural equations of high-income
SC
PR
PN MBI
Private
employees
Own a
motorcycle
Married
status
Have a driving
license
Civil
Employees
Trip
distance
−0.09
0.15* 0.16** 0.15*
−0.12*
0.41**
0.25*
−0.14* 0.15* −0.16**
0.72***
0.49***
SC
PR
PN
MBI
Private employees
−0.03
−0.07 0.13*
0.39***
0.41** 0.75***
0.39***
SC
PR
PN MBI
Own a
motorcycle
Married
status
Trip
distance
0.05
0.08 0.18** −0.19***
0.45***
−0.19 −0.18* 0.67***
0.44***
(a) Structural equations of low-income group (b) Structural equations of low-income group
R2 = 0.56
R2 = 0.52 R2 = 0.50 R2 = 0.23
R2 = 0.64
R2 = 0.46
CMIN/DF = 1.597, GFI = 0.841, AGFI = 0.789,
CFI = 0.913, RMSEA = 0.073
CMIN/DF = 2.026, GFI = 0.759, AGFI = 0.692,
CFI = 0.835, RMSEA = 0.096
CMIN/DF = 2.45, GFI = 0.709, AGFI = 0.642, CFI = 0.741, RMSEA = 0.116
Figure 5. Standardized estimates of three income groups’ structural models.
5.7. Policy Implications
The ANOVA and SEM results depict that the differences exist among three economic
groups of the samples in their behavioral intentions towards the metro-bus service consider-
ing travelling alone, moral obligations, parking restrictions, and metro-bus incentives. The
respondent’s behavioral intentions remain the same across the three groups when they are
travelling with family members which are on the lower side. It implies that traveling alone
and traveling with family members is a significant personal constraint which determines
the mode choice intentions of the local people. This fact can be attributed to the security
and privacy concerns of the people because sometimes people do not feel comfortable
on the public transport when they are travelling with their family members especially fe-
males [
54
,
55
,
78
]. There is a need to provide some service benefits such as assuring security

Sustainability 2022,14, 2654 15 of 19
and privacy of the female passengers and economic incentive schemes for the families to
enhance the use and ridership of the metro-bus service.
Metro-bus incentives, such as the reduced travel time and cost, better access, spatial
coverage, and better comfort through assured seat, would be useful in attracting the
potential users and changing the behavioral intentions. These incentives are usually
helpful in improving the transit ridership and travel comfort of the passengers [
38
]. These
incentives schemes are required to be implemented along with the disincentives on use of
private car such as parking management programs. This research implies that through the
intervention of increased parking fees, commuters showed a positive inclination towards
the use of the metro bus system. Therefore, the traffic management authorities (such as
Traffic Engineering and Planning Agency, Lahore Development Authority) must consider
soliciting a parking management system to discourage the use of the private car through
the implementation of parking fee, especially alongside the metro-bus route. It is believed
that the excess of parking spaces encourage travelers to use private transport; therefore,
limiting parking spaces near the metro route would help to discourage the use of private
car and promote the use of metro-bus [
79
,
80
]. An integrated approach is required in
implementing the incentive and disincentive Traffic Demand Management (TDM) measures
to improve their effectiveness in reducing the traffic congestion and enhancing the use of
the transit system.
The findings of this research study imply that most of the respondents showed a
positive moral obligation towards the environment protection and preserving the natu-
ral resources. Therefore, a good consideration of air quality improvement and policies
pertinent to the climate change impact can be recognized with the promotion of better
public transit systems in the city. The personal norms and social concerns usually help in
shaping the sustainable travel choices among people [
5
,
49
,
70
]. Improved transit facilities
with incentive schemes and parking restrictions on the use of private car would help in
developing the transit-oriented attitudes among the travelers and moral obligations to use
environmentally friendly transport modes. The policymakers should think of ways for
providing safe and comfortable public transport using eco-vehicles which contribute less
emission in the eco-system. Better environmental quality can be mandated by removing
the old conventional bus fleet and replacing it with a better public transport system such
as the metro-bus system. The cognitive variables play an important role in defining the
sustainable travel behavior and traveler’s awareness about the metro-bus benefits can be
helpful in shaping the positive perceptions and behavioral intentions of the commuters [
81
].
In order to avoid an increase in the use of private transport in the coming months, attention
must also be paid to the changes in the modal choice and frequency experienced during
the recent COVID-19 pandemic due to the restrictions imposed by the governments. In
addition, pervasive fear of infection and feeling of stress aboard public transport in the
pandemic is also a concern [
82
,
83
]. Therefore, it is also required to create awareness among
general public about the benefits and incentives associated with the use of metro-bus
service such as awareness campaigns which should focus on improving the perceptions
towards the use of public transport.
6. Conclusions
The government policies to develop and improve the public transport facilities usually
help in the model shift and reduce the traffic congestion. Additionally, the economic
disincentives on use of private car and parking restrictions can help reduce the use of
private transport and shift people towards public transport. However, this model shift is
influenced by several factors, including individual’s personal and social constraints, service
quality of the transit facilities and road infrastructure characteristics. This study attempted
to identify the commuter’s behavioral intentions to use the metro-bus service under the
influence of various constraints, moral obligations, incentives, and restrictions. The required
data were obtained with the help of a questionnaire survey and analyzed using ANOVA
and SEM methods. Survey results revealed that the behavioral intentions of the commuters

Sustainability 2022,14, 2654 16 of 19
differ with the social and personal constraints in traveling. The commuters traveling
with their family members would prefer to use the private car and such intentions do
not differ across low-, middle-, and high-income people. However, significant differences
exist between three income groups about their behavioral intentions considering mobility
incentives and specific parking restrictions. The moral obligations of three income groups
also vary across three groups for the reduction in the traffic congestion, air pollution and
conservation of the natural resources.
Parking restrictions, such as limited, far parking and high parking fees, have a signif-
icant influence on the commuter’s behavioral intentions towards the metro-bus system.
Social constraints in traveling, the metro-bus incentives over a private car, and parking
restrictions are significant determinants of commuter’s moral obligations for reduction
in the traffic congestion, pollution and protecting the natural resources. Additionally,
profession, motorcycle ownership, marital status, trip distance, and possession of a driving
license are significant predictors of personal norms to use the metro-bus service. These in-
fluencing factors implicate that parking management measures can be deployed to change
the behavioral intentions and promote the use of transit modes. Commuter’s awareness
and norms can also be handy in developing positive attitudes towards the metro-bus and
other transit modes. The situational constraints result in negative behavioral intentions
towards bus service. Public transport incentive programs for combined traveling of the
family members and elderly people may help in enhancing the use of the transit service.
The public transport incentives over private vehicles are essential to make a significant
model shift from the private modes to public transit modes. The public transport behavioral
intentions are derived from a small sample which may not reflect the perceptions of the
whole population and city. In addition, this study included only a few social constraints,
incentives schemes, and parking restrictions in the evaluation. Future studies may focus
on including various service quality dimensions of the available transit modes, traveler’s
attitudes, privacy, and personality characteristics in assessing the behavioral intentions and
moral obligations.
Author Contributions:
Conceptualization, M.A.J., N.A. and T.C.; methodology, M.A.J. and N.A.; data
collection, N.A. and M.A.J.; data analysis, M.A.J. and N.A.; writing—original draft preparation, M.A.J.,
N.A., T.C., K.C. and G.T.; writing—review and editing, M.A.J., N.A., T.C., K.C. and G.T.; funding,
T.C., K.C. and G.T. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement:
Ethical review and approval were waived for this study, due
to this study being a non-interventional study that did not involve biological human experiments
and patient data. In addition, this study was completely voluntary and non-coercive, and responses
remain anonymous.
Informed Consent Statement:
The respondents were informed that their responses would remain
anonymous and would be used for research purposes only.
Data Availability Statement:
The data can be made available from the corresponding author upon
reasonable request.
Acknowledgments:
This work was supported by the Thammasat Research Unit in Infrastructure
Inspection and Monitoring, Repair and Strengthening (IIMRS), Thammasat School of Engineer-
ing, Faculty of Engineering, Thammasat University Rangsit, Klong Luang Pathumthani, Thailand.
Authors also extend their appreciation to the respondents for their time and efforts to make this
study possible.
Conflicts of Interest: The authors declare no conflict of interest.

Sustainability 2022,14, 2654 17 of 19
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