Question Items for Positive Effects
Variable Abbreviation Question Items Source Measurement Scale
CD1 I have
confidence in finding alternative solution during traffic jam on the road
Sundström and
Albertsson (2012)
Adapted
CD2 I can drive at
night without a problem
Sullivan et al. (2011)
Adapted
CD3 There is a
difference in driving skills between males and females drivers
Jiménez- Mejías et al. (2014)
Adapted
CD4 I never receive
fine despite breaking the traffic law
Mohamed and Bromfield (2017)
Adapted Confidence in
Driving
CD5 I never
experience accidents on the road
Mohamed and Bromfield (2017)
Adapted
Likert- Scale 1-5
EC1 I am worried
about climate change
Alcock et al. (2017)
Adapted
EC2 I minimize the
cost of travel
Sundling et al. (2014)
Adapted
EC3 I am willing to
walk for short destination
Strath et al.
(2007)
Adapted Environment
Consciousness
EC4 I would like the
toll fees collected to maintain the green environment
Mohiuddin et al.
(2018)
Adapted
Likert- Scale 1-5
Social
Responsibility
SR1 I never like
double parking
Wåhlberg et al.
(2011)
Adapted
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Foresight
SR2 I like to keep
my car in the parking box
Wåhlberg et al.
(2011)
Adapted
SR3 I do not have
violent driving behavior while driving
Vahedi et al. (2018)
Adapted
SR4 I do not like one
person one car travel
Whitmarsh (2009)
Adapted
Likert- Scale 1-5
DD1 I do not drive
after drinking alcohol
Alonso et al. (2015)
Adapted
DD2 I prefer heavier
penalty for drive after drinking
Alonso et al. (2015)
Adapted
DD3 I try not to drive with emotions and anxiety
Clapp et al.
(2011)
Adapted Timely
Deviation in Driving
DD4 I do not smoke
while driving
Yannis et al. (2011)
Adapted
Likert- Scale 1-5
SN1 I read or text
messages while driving because others do
Nevin et al.
(2017)
Adapted
SN2 I dial or talk
while driving because others do
Nevin et al.
(2017)
Adapted Subjective
Norms
SN3 I drive after
drinking alcohol since others do
Guerrini et al. (2006)
Adapted
Likert- Scale 1-5
Question Items for Negative Effects
Variable Abbreviation Question Items Source Measurement Scale SS1 I bought a car
because to suit my social status
Kusuma (2015)
Adapted Social Status
SS2 I try not to travel in public
transportations because of my social status
Kusuma (2015)
Adapted Likert- Scale 1-5
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Foresight
SS3 My social status is higher when I own a luxury car
Kusuma (2015)
Adapted
SS4 Public respects me when I travel on a luxury vehicle
Kusuma (2015)
Adapted
AD1 I like driving license to be suspended for speeding
Mann et al.
(2016)
Adapted
AD2 I like drivers' eyes to be check regularly to prevent accidents
Boadi-Kusi et al. (2016)
Adapted Accident and
Damages (Unpleasant)
AD3 I like to have an age limit of 10 years for vehicles
Onyemaechi and Ofoma (2017)
Adapted
Likert- Scale 1-5
W1 I try not to change my lane often while raining
Rasool et al.
(2015)
Adapted
W2 I plan my trip
based on weather conditions
Bohn (2014) Adapted
W3 Bad weather
conditions lead to more air pollution because of regular braking
Thompson (2017)
Adapted Weather
(Unpleasant)
W4 Bad weather
conditions affect smart mobility on the road
Antov et al.
(2010)
Adapted
Likert- Scale 1-5
RI1 I like public transport that is available at all times
Panter et al.
(2016)
Adapted
RI2 I like walking pathway while walking on busy roads
Hull and O’Holleran (2014)
Adapted Road
Infrastructure (Pleasant)
RI3 I want motorcyclist to use their
motorbike lanes at all times
Puratmaja et al. (2017)
Adapted
Likert- Scale 1-5
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Foresight
RI4 I want cyclist to use their cycling lane at all times
Puratmaja et al. (2017)
Adapted
RI5 I like to have traffic police in every busy street during road traffic congestion
Agyapong &
Ojo (2018)
Adapted
RI6 I feel fixed road dividers are an obstacle during road traffic
congestion instead of movable road lane dividers
Naveen &
Sowmya (2019)
Adapted
RI7 I like to have 50 meters road dividers before the exit lanes on highways
Naveen &
Sowmya (2019)
Adapted
RI8 I like upper-tier roads (e.g. LRT, MRT, Flyovers) on every busy road
EuroRAP AISBL (2011)
Adapted
Question Items for Hereditary Effects
Variable Abbreviation Question Items Source Measurement Scale
H1 I drive even for
short distances because of my habit
Henriksson et al. (2014)
Adapted
H2 I habituated driving frequently from my parents
Martin et al.
(2016)
Adapted
H3 I follow my parents to go to job by car only
Brown et al.
(2011)
Adapted Habit
H4 I want privacy when
driving on road following the footsteps of my parents
Owsley et al.
(1999)
Adapted
Likert- Scale 1-5
Mental Block
MB1 Billboard
advertisement on the
Yellappan et al. (2016)
Adapted
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Foresight
road disturbs my driving
MB2 Any gathering of
people on road disturbs my driving
Henriksson et al. (2014)
Adapted
MB3 I am afraid to drive at midnight
Fildes et al.
(1994)
Adapted MB4 I want to overtake
female drivers psychologically
Martinussen et al. (2013)
Adapted
Likert- Scale 1-5
Question Items for Mediator Variable
Intention for Road Commuters Performance (Mediator Variable)
Construct Abbreviation Question Items Source Measurement Scale INT1 I always intend to
drive carefully
Arnau- Sabatés et al. (2013)
Adapted
INT2 I intend to do regular maintenance for my vehicle
Arnau- Sabatés et al. (2013)
Adapted
INT3 I intend to have a smart mobile- connected while driving
Arnau- Sabatés et al. (2013)
Adapted
INT4 I would call myself as not a rash driver
Arnau- Sabatés et al. (2013)
Adapted
INT5 I intend to travel with concern for environmental issues
Alcock et al. (2017)
Adapted
INT6 I intend to drive less frequently to
minimize air pollution
Alcock et al. (2017)
Adapted Intention for
Road Commuters Performance
INT7 I intend to travel strictly following the lane discipline
Smith (2016)
Adapted
Likert- Scale 1-5
Question Items for Dependent Variable
Travel Behavior Performance of Road Commuters (Dependent Variable)
Construct Abbreviation Question Items Source Measurement Scale
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Foresight
TBP1 I prefer to purchase green vehicle like battery cars/
hybrid cars to reduce air pollution
Liu et al.
(2017)
Adapted
TBP2 I am willing to use public
transportation for short distance to improve smart mobility
Liu et al.
(2017)
Adapted
TBP3 I share vehicle with my friends and relatives to reduce trips on the road to improve smart mobility
Javid et al.
(2017)
Adapted
TBP4 I plan my travel to do multiple tasks within a single trip to have smart mobility
Al
Maghraoui (2019)
Adapted Travel
Behavior Performance of Road
Commuters
TBP5 I prefer to walk or cycle instead of using vehicles to improve air pollution
Pooley et al. (2013)
Adapted
Likert- Scale 1-5
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Foresight
1
Title of the Manuscript: Smart Cities need Environmental Consciousness and more Social Responsibilities as an outcome of COVID-19 - Reflections from Urban Road Commuters
Manuscript ID Number: fs-02-2021-0035
No. Comment of reviewers (1) Response to comments of the reviewer (1) 1. Comments:
Abstract
1. Research issue:
Environmental protection through travel behavior 2. Purpose: To examine determinants of travel behavior
3. Design: Underlying theory used is not mentioned
4. Findings were adequately stated.
5. Limitations and
implications were mentioned.
6. Originality: New dimension identified was not clearly mentioned and highlighted.
Thank you very much for your valuable comments and suggestions.
The required amendments were carried out in the revised version of the article.
Page 1, Abstract, Line 11 Purpose
A lesson has been learnt from the pandemic experience that less damages to environment and realizing more social responsibilities would be the direction of post-pandemic period globally. The present study focuses on identifying the appropriate determinants of the proposed urban travel behavior model to develop Smart Mobility in Smart Cities to protect environment. Potential to realize Smart Cities with infrastructure development has been explored in this article if road users are keen to combat climatic change which is clear from the challenges of flattening the infection rate through the enforcement of rules and regulations by the various government.
Design/methodology/approach
The proposed urban travel behavior model includes sub-drivers for each of the main drivers in the Theory of Interpersonal Behavior. These sub-drivers emphasize in forming intentions to perform the behavioral changes while driving on urban roads during COVID-19 and post-pandemic periods. A primary online survey was conducted among road commuters in the most crowded place in Malaysia, the Greater Kuala Lumpur. A total of
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383 respondents who frequently drive on road during the last one year were surveyed for this study. This data analysis of this quantitative study applied PLS-SEM approach to determine the significant findings and results.
Significant Findings of the study
The significant findings of the study reveal that environmental consciousness and timely deviation in driving during traffic congestion are positively and significantly influencing the travel behavior performance of commuters on urban roads. On the other hand, wet conditions due to weather, narrow road infrastructure, and habit of road commuters are negatively influencing travel behavior performance. Social responsibility is positively and significantly influencing travel behavior performance through the mediating effect of the intention of road commuters’ behavior.
Research limitations/implications
The current environmental concerns and societal adherence efforts in breaking the chain of the infectious COVID- 19 among people can be manifested to develop Smart Cities with less air and noise pollution in the future. In this context, the present study proposes an urban travel behavior model and test for its suitability of greener and cleaner environment for the benefits of future generations. The limitation of the present study is that travel hazards are not included in the framework since it is a topic of its own volume.
Originality of the study
It is timely to implement Smart Mobility on road business models for Smart Cities since the consequences of the pandemic make us to realize the importance of environmental concerns and social responsibilities of everyone.
Theory of Interpersonal Behavior (TIB) considers four drivers namely attitude, subjective norm, affect and habit
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3
which induce intention to perform behavioral decision. The novelty of the present study is the development of sub-drivers for these four drivers in the context of urban travel behavior model.
2. Introduction
All comments that have been highlighted in the previous review have been
satisfactorily addressed.
However, please reconstruct your problem statement to clearly state the aim of your paper.
Thank you very much. Problem statement has been reconstructed as suggested by the reviewer in the revised version.
Page 2, Section 1.0, Line 9 1.0 Introduction
For the last three decades, global warming has been a central concern worldwide. One of the primary causes of global warming is the increase of carbon dioxide (CO2) (European Commission, 2018) from urbanization for economic growth (Bekhet & Othman, 2017). The rapid industrialization and frequent traveling ways tend to cause difficulties in accommodating the number of vehicles during peak hours, primarily due to the ineffective nature of public transportations (Kang et al., 2019). Moreover, single-occupied vehicles are strongly habituated and present on road (Kang et al., 2020), indicating more number of vehicles on road (International Organisation of Motor Vehicle Manufacturers, 2019), causing road traffic congestion. These habitual behaviors not only increase fatal accidents and environmental pollution on road but also limit the sharing of vehicles among commuters which are pivotal to the present research. Further, the existing transportation system needs to evolve and develop for future Smart Cities to be environmentally and technologically viable. For instance, Neckermann (2015) stated that accidents occur due to human errors, and it accounts for 90 percent. Hence, human driving behavior needs to be changed to avoid future fatal damages to the environment and human beings. In the year 2018, the Malaysian government provided road facilities, hosted about 22% of the 30 million population of Malaysians (Ramakreshnan et al., 2018). On the other hand, the Ministry of Transport has increased 128% of the length of the railroads and
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125% of roads. The severity of road traffic congestion and lack of practice for Smart Mobility for decades is due to lack of urban travel behavior models for Malaysia (Jayaraman et al., 2019; Leow et al., 2018). An urban travel behavior model is necessary for road users to travel safely with pleasantness by minimizing these issues.
Moreover, Malaysians have considerable awareness of the environment (Masud et al., 2015), but they do not change their mode of transport, creating more carbon footprints. Future visions such as sharing resources and mobility space integrated with advanced technologies to create Smart Cities (Zahraei et al., 2019). However, convincing both policymakers and societies to fully embrace Smart Cities remained in doubt (Yigitcanlar et al., 2019). Despite barriers to Smart Cities, the untapped opportunities for sustainable environment development should be explored (Angelidou et al., 2018). It is challenging to predict road traffic congestion. Innovative and rapid research on the new traveling behavior can be expected to reduce road traffic congestion (Nagy & Simon, 2018). Smart Mobility is one of the components of Smart Cities and it involves three stages (Neckermann, 2015), the first stage will be quite accomplished, which is called Zero Emissions. The second stage will be the development of autonomous electric vehicles that can travel in a straight line and with minimum distance between other vehicles targets Zero Accidents. Lastly, Zero Ownership will complete ‘Smart Mobility’ when the utilization of public transportation is increased to a large margin. The recovery from creating excess carbon emissions should be prioritized to preserve the environment. In turn, the significance of the present study is in contributing to the literature ‘new norms’ for travel behavior which will enhance environmental safety and smart mobility on road to build smart cities.
3. Literature Review
The issue being studied in the context of Malaysia has been satisfactorily discussed. The underlying theory used as a
Thank you very much
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5 basis to develop the
conceptual framework has also been described.
4. Conceptual Research Framework
1. The consistency between the title of the paper, research issue, and research gaps with the conceptual research framework has been addressed.
2. For the convenience of your reader, it is advisable to include a short paragraph presenting definitions, conceptualizations and operationalizations of each construct.
3. Research hypotheses were appropriately developed based on the conceptual framework.
A short paragraph presenting definitions, conceptualizations and operationalizations of each construct has been added as per the reviewer’s valid comments. Thank you very much.
Page 4, Section 2.0, Line 33 2.0 Literature Review
During peak office hours, the occupied road lanes are fragile towards accidents, tensed emotions supplemented by the frequent rains in Malaysia. Aggressive driving and road rage are common among young Malaysian drivers, leading to loss of control to their vehicles (Adnan et al., 2017). Road users do not abide by the road laws that could minimize the potential hazardous situations while traveling (Oxley et al., 2018). Public transportations in Malaysia are not adequately used by commuters because of lack of privacy and convenience. Hence, location coverage is limited, and the psychological perceptions of public transport are poor (Loo et al., 2015). The travel behavior of road users is worth studying because of their experiences can leverage to improve safety measures, smoothen the flow of traffic, and proper use of public transports. The Theory of Interpersonal Behavior (TIB) by Triandis (1977) was adapted in the present study. There are four main predictors, namely, attitude, social factors, affect and habit in TIB. Attitude was considered as perceived consequences; social factors are norms, roles, self- concept, affect is emotions, and habit is practices. The present study uses the work of Jayaraman et al. (2019) with modifications to their research framework. Some constructs are merged into positive predictor whereas remaining constructs are merged in to negative predictor and habit as the hereditary predictor. The level of confidence while driving determines cases such as discrimination among genders and the safety of road commuters, which will pose a certain level of threats to others while driving on the road. According to Jiménez-Mejías et al. (2014), both
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males and females have different driving behavior and styles. Therefore, it is not surprising when such contrasting driving styles between males and females create accidents or rash decisions on the road. When road users are not parking their vehicles properly, this will cause extended cruising time and the expense of resources for entering, parking, and exiting in the area (Antolín et al., 2018; Małecki, 2018). Further, well-designed car parks are worth mentioning (Małecki, 2018) for reducing carbon emissions. Timely deviation in driving is a common sight when alcohol driving (Watling et al., 2018), mobile phones usage on driving (Yannis et al., 2011), hostile behaviors (Clapp et al., 2011), and negative emotions on driving (Scott-Parker et al., 2018) are influencing the road users negatively. Also, offenses like text-and-drive, answering, and dialing phone calls are usually influenced by social norms. Social status seekers are symbolized as a person who is highly educated, having fame, and high income (Choo & Mokhtarian, 2004; Gilmore & Patwardhan, 2016). When road users wanted more mobility, they will choose private vehicles, which may cause risks to accidents and damages to others and the environment (Gilmore
& Patwardhan, 2016). The traveling time and plans of road users could be severely affected by weather conditions (Antov et al., 2010). Even though road infrastructures can help reduce air pollution (Faria et al., 2019) and increase physical travel (Panter et al., 2016), usage of the facilities is low (Ramakreshnan et al., 2018). If this is the case, road commuters will mainly experience heavy road traffic congestion during peak hours. Another reason is that driving in South East Asia depends on location, cultural determinants, and socio-demographics (Loo et al., 2015).
It is the location of Klang Valley, where it is the most populated area in Malaysia that consists of Petaling Jaya, Shah Alam, and Klang–three major Malaysian cities (Omar, 2014). It is also primarily due to road users' socio- demographics, where they are capable of spending on private vehicles due to low interest rates (Leow et al., 2018).
The positive attitude of commuters while driving on road is characterized by Confidence in Driving (CD), Environment Consciousness (EC), Social Responsibility (SR), Timely Deviation in Driving (DD), and the
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supporting role of fellow commuters via Subjective Norm (SN) were classified under positive effects in the proposed conceptual framework. On the other hand, Social Status (SS) for pride, Accident and Damages (AD), bad Weather (W), and poor Road Infrastructure (RI) were categorized under negative effects. Following the ancestor way of practices is considered as a hereditary effect Habit (H). The following section depicts the conceptualization of the framework based on these effects.
5. Research Method
The research methodology section is now adequately sufficient to allow for replicability. Sampling technique, sample size, instrument development, data collection method are now elaborated clearly.
Thank you very much
6. Data Analysis and Findings 1. All information regarding outer loading, CR and AVE, and VIF are now clearly presented.
2. Each item/indicator used is now presented in Appendix 1.
3. Discriminant validity is now presented in Table 5.
4. Your path diagram is now clearly presented.
Thank you very much
7. Discussion
1. Your findings are now being discussed clearly.
Thank you very much
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8 2. Conclusion was consistent
with other parts of the paper.
8. Additional Questions:
1. Originality: Does the paper contain new and significant information adequate to justify publication?: Yes. The paper contributes to knowledge advancement by filling the knowledge gap identified from the literature.
Thank you very much
9. 2. Relationship to
Literature: Does the paper demonstrate an adequate understanding of the relevant literature in the field and cite an appropriate range of literature sources? Is any significant work ignored?: The study is an extension of the work of Jayaraman et al (2019).
Thank you very much
10. 3. Methodology: Is the paper's argument built on an appropriate base of theory, concepts, or other ideas? Has the research or equivalent intellectual work on which the paper is based been well designed? Are the methods employed appropriate?: The research method has now been
Thank you very much
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