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Questionnaire

Dalam dokumen Foresight - Taylor's University Research (Halaman 35-50)

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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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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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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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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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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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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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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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

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