Ensuring traffic safety of cargo motorcycle drivers in last-mile delivery services in major Vietnamese cities An Minh Ngoca,b,*, Hiroaki Nishiuchia, Nguyen Thi Nhub, Le Thu Huyenb aSch
Trang 1Case Studies on Transport Policy xxx (xxxx) xxx
Available online 14 July 2022
2213-624X/© 2022 World Conference on Transport Research Society Published by Elsevier Ltd All rights reserved
Ensuring traffic safety of cargo motorcycle drivers in last-mile delivery
services in major Vietnamese cities
An Minh Ngoca,b,*, Hiroaki Nishiuchia, Nguyen Thi Nhub, Le Thu Huyenb
aSchool of Systems Engineering, Kochi University of Technology, 185 Tosayamadacho-Miyanokuchi, Kami City, Kochi 782-8502, Japan
bFaculty of Transport Economics, University of Transport and Communications, 3 Cau Giay, Lang Thuong, Dong Da, Hanoi 100000, Viet Nam
A R T I C L E I N F O
Keywords:
Cargo motorcycle
Traffic crash
Last mile delivery
Safety
A B S T R A C T The prevalence of cargo motorcycles (cargo MCs) is rapidly changing urban freight transportation in Vietnamese cities As the dominant mode of transportation in last-mile delivery (LMD) services in Vietnam, cargo MCs are found throughout the country However, little is known about the risk of crashes involving cargo MC drivers, the factors affecting road crashes, and the perceived risk of crashes among cargo MC drivers This information is vital given the rising safety concerns and the economic losses due to traffic crashes in the country
This study characterized traffic crashes involving cargo MCs as being either minor or major Specifically, our survey of 726 cargo MC drivers in Hanoi showed that 42.01% of respondents had experienced a crash within the last year, and 13.37% of respondents had been involved in at least one major traffic crash Competition for work and unsafe driving behavior were the main reasons underlying these risks Crash severity varied depending on the number of years that the drivers had worked in LMD, job type, income perception, delivery pressure, smoking and drinking habits, and mobile phone usage Major crashes were also associated with the distance travelled daily and the number of trips to the distribution hub Conversely, working overtime, lack of rest stops, daily order status, and traffic violations were associated with minor crashes These findings suggest that cargo MC drivers face numerous risks and that efforts to address these challenges are urgently required in order to promote the adoption of sustainable and healthy shipment practices
1 Introduction
In major Vietnamese cities, cargo motorcycles (cargo MCs) are a
relatively new mode of cargo transportation that is rapidly changing
urban logistics Widely considered to be a convenient, fast, and efficient
mode of cargo transportation for last mile delivery (LMD), cargo MCs are
popular among urban cargo carriers A recent traffic survey conducted
by the University of Transport and Communications (UTC) in three
Vietnamese cities found that cargo MCs accounted for as much as 11 %
of traffic flow, while the maximum share of trucks was only 2.75 %
(UTC, 2020) Their results also showed that cargo MCs have overcome
the disadvantages of vehicle typology (i.e., weight and volume
limita-tions) to become a highly favored mode of cargo transportation in the
urban logistics industry
Despite the ubiquitous nature of cargo MCs on Vietnamese streets,
information about the trends in cargo MC use in Vietnam is limited
Since cargo MCs do not need to be registered to carry goods, city
governments do not know how many cargo MCs are active in the urban cargo transportation sector As a result, developing a traffic safety plan for urban freight transportation activities is difficult
Studies on trends in cargo MC use and road traffic crashes are also limited, and most previous research has focused on fatalities and injuries involving trucks (Clifton et al., 2009; Giuliano et al., 2013; McDonald
et al., 2019; Pokorny et al., 2017) In Vietnam, where this study was conducted, research on the road traffic safety of motorcycles has increased in recent years (Bui et al., 2020; Ngoc and Thanh, 2019, 2020; Ngoc et al., 2021; Nguyen et al., 2021; Nguyen-Phuoc et al., 2020a,b; Truong et al., 2018, 2020) However, most of this research has focused
on passenger MCs and not cargo MCs To the best of our knowledge, no empirical studies have focused specifically on road traffic crashes involving cargo MCs This study, therefore, provides a valuable starting point, given that many of the vehicles used to transport cargo in cities are cargo MCs
In this study, we characterized road traffic crashes involving cargo
* Corresponding author
E-mail addresses: an.ngoc@kochi-tech.ac.jp, anminhngoc@utc.edu.vn (A.M Ngoc), nishiuchi.hiroaki@kochi-tech.ac.jp (H Nishiuchi), nhunguyen@utc.edu.vn
(N.T Nhu), lthuyen@utc.edu.vn (L.T Huyen)
Contents lists available at ScienceDirect Case Studies on Transport Policy journal homepage: www.elsevier.com/locate/cstp
https://doi.org/10.1016/j.cstp.2022.07.004
Received 21 March 2022; Received in revised form 5 July 2022; Accepted 11 July 2022
Trang 2MCs with evidence obtained from a survey of logistics companies in
Hanoi The survey examined both the incidence of crashes, and the
factors affecting road traffic crashes while transporting goods The
findings presented here focused on human factors instead of other
causes, and it is hoped that the results will contribute to the
develop-ment of a foundation for future research and for managing cargo MCs In
addition, the findings can provide insights into cargo MC usage and the
associated potential risks that can help policymakers, and carriers better
understand the challenges facing cargo MC drivers (e.g., unsafe driving
practices) and help them ensure the safety of cargo MC drivers in urban
areas
2 Literature review on traffic crashes
This study explores the risk of crashes involving cargo motorcycles
involved in urban freight transport Specifically, we focused on the
personal behaviors and work conditions that affect the incidence of road
crashes involving cargo MC drivers Here, we present an overview of
literature that focuses on the road safety of urban freight and how this is
affected by personal behaviors
Safety studies have conventionally assessed the impact behavioral
factors on road crashes by dividing such behaviors into the following
four categories: demographic characteristics, driving behavior, work
conditions, and perceived environment
2.1 Demographic characteristics
Demographic characteristics relate to all personal factors, e.g., socio-
demographics, driving ability, and availability of mobility resources
Socio-demographics of cargo MC drivers have been investigated
exten-sively in previous studies A previous study reported that males are more
likely to experience nonfatal injures in the cargo transportation sector
(McDonald et al., 2019) Young and inexperienced workers were more
likely to be involved in crashes (Shope and Bingham, 2002, Fisher et al.,
2002)
2.2 Driving behavior
Numerous studies have confirmed that driving behavior plays a role
in the incidence of crashes by drivers (Bazargan-Hejazi et al., 2013; Bui
et al., 2020; Hassanzahed et al., 2020) For example, drinking while
driving was strongly associated with risky driving behavior (Faried
et al., 2017; Ngoc et al., 2012; Nguyen et al., 2013; Vu et al., 2020) In
addition, smoking and mobile phone use while driving were also
re-ported to affect the incidence of crashes (La et al., 2013; Nguyen et al.,
2020; Truong et al., 2018) Mangiaracina and Palumbo (2007) and
Merrill (2019) reported that drivers were more distracted by smoking
while driving, and that smoking constitutes a considerable risk to road
safety At a more general level, Shope and Bingham (2002) reported that
the use of mobile phones or electronic devices, as well as eating,
drinking, smoking or interacting with others, all contributed
signifi-cantly to distracting drivers; as a result, drivers were more likely to be
involved in traffic crashes
2.3 Work conditions
Work conditions, including driving time, rest time and work
per-formance, were all significantly associated with fatigue and the risk of
the crashing Baas et al (2000) reported that fatigue is related to 5.1 %
of fatal road crashes among truck drivers in New Zealand, whereas
Torregroza-Vargas et al., 2014 reported that 33 % of traffic crashes
involved drivers with long work hours (12 h or more) Other studies
identified a positive relationship between major crashes and fatigue or
stress in the workplace (Doustmohammadi, 2019; Hartley and Hassani,
1994; Lagarde et al., 2004)
2.4 Perceived environment
The physical environment has been shown to markedly affect risky driving The presence or absence of major roads and large road crossings may cause the traffic problems and increase the risk of crashes (Barua
et al., 2014; Guo et al, 2017;) In a survey of light freight vehicles and short-haul drivers in Australia, Friswell and Williamson (2010) reported that the majority of drivers were more likely to be involved in crashes when driving in very heavy traffic or under poor road conditions Barua
et al (2014) reported that the risk of crashes was positively associated with the number of intersections and crosswalks without signals The prevalence of crashes was also significantly associated with intersection geography, the number of turning movements, and signal phases (Guo
et al., 2010)
However, little is known about the impact of the physical environ-ment on drivers’ perceptions when they drive, and how these percep-tions influence the way they drive Driver’s perception of danger, the likelihood of crashes, the quality of the road infrastructure, and other characteristics of the physical environment are all considered to influ-ence driving risk and, therefore, the safety of driving
2.5 Conclusions of the literature review
Overall, the literature review revealed that the majority of studies conducted to date have examined the underlying reasons for crashes in the urban freight transport sector However, many of these studies focused on the reasons for crashes involving truck drivers, and little attention has been paid to the safety of cargo MC drivers Vietnam is characterized by having large and diverse motorcycle-using de-mographic, a relatively basic and largely incomplete motorcycle traffic infrastructure, and an unsafe driving environment Research on traffic safety as it relates to cargo MCs in Vietnam will facilitate comparisons with countries that have a fewer cargo MC crashes In addition, the findings might promote the development of quantitative measures that can be applied to strategies and policies for improving the safety of cargo
MC drivers
3 Background
Urban cargo vehicles in Vietnam can be classified into five cate-gories: mid-sized trucks (7.5–16 tons), small trucks (3.5–7.5 tons), light
commercial vehicles (<3.5 tons), motorcycles (two- or three-wheelers),
and bicycles Two-wheeled motorcycles (also called cargo MCs, see Fig 1) are the most commonly used cargo vehicles in Vietnam Since they are also the most important vehicle segment for LMD in the country, the focus of this section is on this vehicle segment
Cargo MCs have proven to be cost-effective for LMD activities, especially when compared to vans or trucks Their small size means that they can move through traffic easily and park in a variety of areas, including on sidewalks In addition, the poor accessibility of streets in the city center, which are mostly narrow and have high traffic densities, makes driving trucks difficult In these areas, cargo MCs have a very large competitive advantage in that they can more easily meet the time- sensitive requirements that are typically required for deliveries by receivers
As an agile and convenient form of freight transport, cargo MCs can transport payloads of up to 350 kg Such vehicles are well suited to mail and parcel delivery services, food delivery, and services that require the delivery of small packages However, no official cargo MC platform has been adopted in Vietnam to date In Vietnam, as defined in the law (QCVN 41:2016, Circular 06/2016/TT-BGTVT), a motorcycle is considered to be any two-wheeled vehicle with a weight not exceeding
400 kg that is powered by an engine with a cylinder capacity of at least
50 cm3 In the area of freight transport, goods loaded onto a motorcycle must not exceed the cargo bracket designed by the manufacturer, which
is typically 0.3 m to the sides and 0.5 m to the rear The height of goods
Trang 3Case Studies on Transport Policy xxx (xxxx) xxx
from the road surface must not exceed 1.5 m However, since there is no
standardized design for such brackets, cargo MCs often face problems
associated with safe and efficient operation
In 2020, the UTC conducted surveys as part of implementing a pilot
project for using electric vehicles for LMD services in Vietnam (UTC,
2020) The findings showed that cargo MCs are generally popular, are
seen as providing a valuable service in connecting warehouse facilities
to residences, and fulfill the increasing demand for urban deliveries
Further, in a representative sample, approximately 70 % of the vehicles
used for LMD were motorcycles, followed by trucks of different sizes (24
%) In addition, 95 % of the cargo MCs in the UTC sample were owned by
the driver and only 5 % were owned by companies A separate traffic
survey of 40 road segments in Hanoi found that cargo MCs accounted for
11 % of traffic flow and contributed to 12 % of vehicular congestion
However, since the majority of freight vehicles are active after and
before the peak morning and afternoon/evening congestion periods,
respectively (UTC, 2020), cargo MCs are not considered to pose a serious
problem for road congestion Although the UTC study is one of the only a
few to have examined the activity patterns of freight vehicles, it did not
provide insights into road traffic crashes involving cargo MC drivers in
Vietnam
With the support of logistics companies, we conducted an online
survey of cargo MC drivers at 15 logistics companies in Hanoi from
October 20–30, 2021 These companies are responsible for delivering
goods from local warehouses or fulfillment centers to customers Hanoi
was selected for the following reasons First, since the study team had
experience in observing the movement of cargo MCs on the streets of
Hanoi, the team was able to ensure a high level of survey quality
Sec-ond, e-commerce and online shopping in Vietnam is growing at a
double-digit pace, leading to a marked increase in the demand for urban
deliveries As a result, logistics companies employ a large number of
cargo MCs to transport goods The numerous cargo MCs on the roads of
Hanoi has contributed to a considerable increase in road traffic crashes
Third, data and information on road traffic crashes involving cargo MCs
are scarce, which makes it relatively difficult for concerned
policy-makers to deal with traffic safety issues The findings of this study will
thus enable policymakers to obtain more accurate information
4 Data and methods
4.1 Survey compilation and recruitment
The compilation of the questionnaire was undertaken based on a
literature review of current MC-related research (e.g., Bray and Holyoak,
2015; Chu et al., 2019; Ngoc et al., 2021; Ngoc and Hung, 2019; Thanh
and Ngoc, 2020) and previous related work on traffic safety related to
MCs (Bui et al., 2020; La et al., 2013; Ngoc and Thanh, 2019; Nguyen
et al., 2021; Nguyen-Phuoc et al., 2020a,b; Truong et al., 2018, 2020)
Although the studies described above focused on passenger MCs, several
of the survey items could be adapted to the context of this study The survey included approximately 31 items and focused the following categories:
• Socio-demographic factors
• Employment status and working conditions in the LMD industry
• Behavior of cargo MCs drivers while driving
• Previous experience of crashes among cargo MC drivers while driving
• Perceptions of safety by cargo MC drivers while driving
4.2 Sample size
With the support of managers at logistics companies, we adminis-trated an online survey via the Zalo mobile application (VNG, Vietnam)
to 800 cargo motorcycle drivers from 15 logistics companies collecting from October 20–30, 2021 The purpose of the survey was to charac-terize drivers’ current cargo trips and crash experience The survey was conducted using a random sampling method, in which cargo drivers are randomly selected to participate in the survey The specific number of drivers was proportional to the number of employees at each company (i.e., 15 % of the total number of drivers working at the logistics com-panies) A total of 800 responses were received (response rate: 100 %) of which 726 were complete and analyzed in this study
4.3 Methods
Data analysis was performed using the statistical software program, STATA 16 (http://www.stata.com, College Station, Texas 77,845 USA) Statistical analysis included Chi-square and Kruskal Wallis tests, as well
as analysis using a multinomial logit (MNL) model Regarding the sample size for the MNL model, Schwab (2002) reported that a mini-mum of 10 cases per independent variable was accepted for using the MNL model Part of the survey analysis involved a segmentation of re-spondents based on crash prevalence to examine the perspectives of respondents Respondents were categorized depending upon whether they had any crash experience and, if so, the severity of any crashes in the previous year It was noted that the number of crashes resulting in serious damage to the vehicle or goods, as well as the number of crashes resulting in human casualties, was small To maintain a meaningful sample size, crashes that resulted in severe damage and/or casualties were merged into a single category (i.e., major level crashes) Conse-quently, the following three crash categories were considered in this study: no crashes, minor crashes, and major crashes
• No crash (n = 324, 44.62 %): respondents who have never had a crash while driving a cargo MC in the last year
Fig 1 Example of cargo motorcycles in Hanoi Source: Authors
A.M Ngoc et al
Trang 4•Minor crashes (n = 305, 42.01 %): respondents who were involved in
a crash in the last year, but the crash caused only minor damage to
the vehicle or goods
•Major crashes (n = 96, 13.37 %): respondents who were involved a
crash that caused serious damage to the person, vehicle, or goods
To learn more about our survey respondents, we included items
about age, monthly income, education level, marital status, and whether
or not they possessed a vehicle license As our study aimed to understand
the factor(s) associated with road traffic crashes and the perceived risk
related to cargo MCs, information about travel behavior and poor
driving habits was also recorded
The independent variables could be classified into four categories:
(a) socio-economic characteristics, (b) work conditions, (c) driving
behavior, and (d) risk perception More specifically, socio-economic
characteristics included age, education, personal income, marital
sta-tus, and possession of a vehicle license Work conditions involved
employment status (i.e., years of driving, and working full-time), work
environment (i.e driving time, rest time, daily order status, daily
dis-tance, and stress levels) Driving behaviors included smoking, driving,
using mobile phone, or illegal driving Risk perception included
infor-mation regarding a driver’s perception of road infrastructure The
dependent variable was crash experience and had three levels: no crash,
minor crash and major crash
5 Results and discussion
5.1 Characteristics of respondents
Table 1 shows the socioeconomic characteristics of the respondents
and their crash experience The results showed that there were
statisti-cally significant differences among the three levels of crash-experience
categories for age, education, income, marital status, and possession of
a vehicle license For example, the highest prevalence of no crashes and minor crashes was observed among respondents aged 25–40 Re-spondents with higher education level were significantly more likely than those with lower education level to have a major crash (p ≤ 0.05)
In addition, significant differences were observed between crash expe-rience and monthly income, with the highest prevalence of major crashes experienced among respondents with monthly incomes in the range VND 10–15 million Marital status appeared to be related to crash experience, with married drivers being significantly (p ≤ 0.001) less likely than unmarried drivers to be involved in a traffic crash Finally, respondents in possession of a motorcycle license were more likely to be involved in a traffic crash
5.2 Crash experience relative to work pressure and driving behavior
Given that human behavior constitutes the principal cause of motor vehicle crashes (Petridou and Moustaki, 2001; Williams and O’Neill, 1974), we asked the respondents to describe their mental health and routines while driving In addition, we recorded the daily distance travelled, work hours, number of orders, number of return trips to the distribution hub, and perception of their salary Table 2 shows the re-sults of the MNL regression analysis Looking at the model fit statistics,
the likelihood ratio (LR) test was significant (p < 0.001), meaning that at
least a subset of the predictor has non-zero effects Overall, these results indicated a good model fit
Crash severity varied depending on the number of years working in the LMD sector, the type of job, perceived sufficiency of income, pres-sure to meet delivery deadlines, and smoking, drinking, and mobile phone usage while driving Aside from these factors, working overtime,
Table 1
Socio-economic characteristics of respondents relative to crash prevalence
No crash (n ¼ 324), %
Minor crash (n ¼ 305), % Major crash (n ¼ 96), % Survey sample (n ¼
726), %
Kruskal Wallis significant p ≤ 0.001
Junior college and
Bachelor’s degree
Kruskal Wallis significant p ≤ 0.05
Less than VND 10
More than VND
Kruskal Wallis significant p ≤ 0.001
Kruskal Wallis significant p ≤ 0.001
Motorcycle
Both motorcycle
and car license 35 39 12 34
Kruskal Wallis significant p ≤ 0.01
Table 2
Results of MNL regression on crash severity
Dependent variables
Employment status
Years of driving in LMD service 1.680 0.093 0.604 0.158
Working full-time (1 = “yes”, 0 = “no”) 0.544 0.351 2.832 0.490
Working environment
Working over 8 h (1 = “yes”, 0 = “no” 4.371 0.284 1.169 0.468
Have no time to take a rest (1= “yes”, 0 =
“ no” 2.776 0.510 1.092 0.499 Daily order status (1 = “50 orders and
above” orders”, 0 = “<50 orders” 0.629 0.273 0.633 0.338 Daily distance driven (1 = “<50 km”, 2 =
“ 50–100 km”, 3 = “100 – 150 km”, 4 =
“ Over 150 km)
0.975 0.112 1.542 0.174
Number of return trips to hub 1.024 0.036 1.085 0.049
Perceived sufficient of salary (1 = “yes”, 0 =
“ no” 0.542 0.255 0.436 0.337 Suffered stress from driving (1 = “yes”, 0 =
“ no” 1.948 0.244 1.001 0.380 Delivery pressure (1 = “yes”, 0 = “no”) 0.587 0.232 2.455 0.373 Driving behavior
Smoking while driving (1 = “never”, 2 =
“ sometime”, 3 = “always” 0.521 0.207 2.289 0.293 Drinking history (1 = “no”, 2 = “before 2 h”,
3 = “before 5 h”, 4 = “before 1 day”) 2.759 0.210 2.430 0.232 Using mobile while driving (1 = “never”, 2 =
“ sometime”, 3 = “always”) 1.355 0.139 0.501 0.224 Traffic violation (1 = “never”, 2 =
“ sometime”, 3 = “always”) 0.579 0.198 1.514 0.299
Model fit
Log-likelihood: − 570.08 Likelihood ratio test
Prob > Chi-square 0.0000
Note: Base reference: “no crash” variable; Estimates (Est.) in bold is significant
at α =0.05; Est in bold italics is significant at α =0.1
Trang 5Case Studies on Transport Policy xxx (xxxx) xxx
lack of rest, large order volumes, stress due to driving, and traffic
vio-lations were largely uncorrelated with the likelihood of a major crash,
although they were strongly associated with minor crashes Conversely,
while daily travel distance was associated with major crashes, this factor
was not associated with minor crashes
Fig 2 shows the aforementioned similarities and differences among
the factors influencing the likely severity of a crash The figure shows the
relative effects of each determinant on crash severity while holding
others in the model constant More specifically, the odds of experiencing
a major crash decreased by 39.6 %, 56.4 %, and 49.9 % due to the
in-fluence of factors such as years of driving, perceived sufficiency of
salary, and mobile phone usage while driving, respectively Conversely,
factors such as job type, daily driving distance, number of return trips,
delivery pressure, and smoking and drinking history were positively
associated with major crash experience, with an increase in the odds of
183.2 %, 54.2 %, 8.5 %, 145.5 %, 129 %, and 143 %, respectively It is
surprising that job type was the most influential factor affecting the
incidence of major crashes This finding may be explained by the fact
that when a driver works full time, they are forced to drive during rush-
hour traffic every day As a result, the overall quality of their driving
decreased rapidly and their driving behavior became increasingly
dangerous The variable “delivery pressure” corroborated this
assump-tion, as it was also found to be significantly associated with the
likeli-hood of a major crash (p < 0.001) The estimate of “delivery pressure” is
2.455, which suggests that if drivers indicate that they are under
pres-sure to fulfil daily orders, the odds of being involved in a major crash is
approximately 145.5 % higher than drivers who are not under pressure
In terms of outcomes of minor crashes, the findings showed that one
of the key factors associated with experiencing a minor crash was long
work hours In addition, a lack of rest time and drinking history were
found to be positively associated with minor crash experience
Specif-ically, the odds ratio of being involved in a crash due to long working
hours, lack of rest, and alcohol drinking history increased by 337 %, 178
%, and 176 %, respectively, suggesting that a stressful working
envi-ronment and the habit of using alcohol not only threaten the physical
and mental health of employees, but they also contribute to potentially
risky behavior that may result in crashes Other variables such as “stress
due to driving”, “years of experience”, and “using a mobile phone while driving” were also positively associated with minor crashes The odds of
a minor crash increased by 95 % in drivers with experience of stress, a one-unit increase in working years was associated with a 68 % increase
in the odds of minor crashes, using a mobile while driving increased the odds of minor crashes by 36 % While previous studies have proposed that inexperienced drivers contribute markedly to traffic crashes, the results of this study show that road traffic crashes can increase even when LMD services are performed by experienced cargo MC drivers; fortunately, however, these drivers were not involved in major traffic crashes
5.3 Risk perception among cargo MC drivers
Perceived risks were further explored by asking drivers who had, and who had not, experienced crashes to respond to the following item:
“Regarding crashes, how safe do you think the city of Hanoi is?” Re-sponses comprised the following five-point Likert scale: ‘very unsafe’,
‘unsafe’, ‘average, ‘safe’, and ‘very safe’ Only 8.26 % of respondents reported feeling ‘safe’ or ‘very safe’ while driving However, the overall perceived safety of cargo drivers was not significantly different among
drivers that had and had not experienced crashes (p > 0.1)
Further-more, no significant differences were observed between the two types of drivers for age, education, income, marital status, and possession of a vehicle license
Respondents were also asked, “What is the main problem with the road infrastructure in Hanoi?”, and they could select more than one answer Fig 3 shows that the respondents had different opinions regarding the road infrastructure However, no significant differences were observed between drivers, irrespective of whether or not they had been involved in a crash
6 Discussion
This study evaluated the risk of crashes in cargo MC drivers active in the LMD sector To the best our knowledge, this is the first such study to
be undertake in Vietnam The findings of this study are particularly
Fig 2 Relative influence of factors affecting MC drivers relative to crash experience
A.M Ngoc et al
Trang 6relevant given the considerable policy interest and investment in
infrastructure over the last two decades that has focused on increasing
road safety For example, the national government of Vietnam spent
more than VND 500,000 billion on transport infrastructure during the
period 2016–2020 (Ministry of Planning and Investment MPI, 2021)
Recent legislation was passed to authorize the use of 100 % of the
rev-enues derived from traffic safety fines on national safety programs As a
result, considerable improvements have been made in road
infrastruc-ture (particularly in the area of traffic safety through measures such as
traffic-calming measures) These improvements and initiatives have
remained a major focus of the traffic safety planning programs in
Vietnam
Conversely, driving safety and training programs in Vietnam are
largely community-driven; however, sometimes these organization
collaborate with transport authorities or receive government funding
These education programs have typically emphasized theoretical
as-pects of safety as opposed to practical asas-pects of safety, and recent
studies reported that these initiatives have had a moderate impact, at
best, on driving safety (NTSC, 2017; Nguyen et al., 2021) There is thus a
need for comprehensive research initiatives that focus on improving our
knowledge of cargo MC driver behavior, as this could be applied to the
preparation of future safety plans and the revision of existing safety
plans
Furthermore, the current attention on driving safety and training
programs only benefits MC users who use motorcycles to commute,
which means that most cargo MC drivers are excluded from these
in-terventions Clearly, there are clearly distinct mobility cultures within
the commuter and cargo MC driver communities – these differences
need to be satisfactorily resolved and understood with the aim of
developing effective and targeted interventions for cargo MC drivers
The findings of this study provide insights into the potential risks
asso-ciated with urban freight transport Below, the research findings and
several policy implications are discussed
Previous studies have consistently reported that urban freight
transportation modes are responsible for a considerable number of
crashes (Doustmohammadi, 2019; Giuliano et al., 2018; McDonald
et al., 2019) The primary reason for major crashes is often fatigue or
stress in the workplace (Doustmohammadi, 2019; Hartley and Hassani,
1994; Lagarde et al., 2004) Driving under pressure can lead to a
dangerous loss of focus, as well as increase the odds of making poor
decisions The results of this study support this hypothesis and show
that, in general, delivery pressure was the main reason for being
involved in a crash when transporting goods In addition, major crashes were more likely to occur when driving distances were long, which is another cause of fatigue The pressure to meet short and tight delivery deadlines and make their return trips on time normally forces most cargo MC drivers to be on the road for extended periods With driver fatigue increasing due to the long hours spent driving, drivers become less attentive and cognizant of road safety Consequently, the incidence
of reckless and negligent driving increases and so does the likelihood of crashes This phenomenon was corroborated by other variables in the model which were also statistically significant; for example, “number of
return trips to distribution hub” (p < 0.1) and “working full-time” (p <
0.05) The estimated “number of return trips” and “working full-time” were 1.085 and 2.832, respectively (Table 2), suggesting that if drivers’ return trips increase or they work full-time, the odds of having a major crash are 8.5 % and 183 % higher than drivers who have fewer return trips or who do not work full-time, respectively Conversely, working overtime and not having time to take a rest were both positively asso-ciated with minor crashes among cargo MC drivers These findings show that these improvements in workplace conditions by logistics com-panies, including decreasing workloads and increasing support from peers and supervisors, could mitigate the risk of crashes among target employees
In addition to workplace stress, risky driving behavior has been identified to be a major factor responsible for road traffic crashes (Bazargan-Hejazi et al., 2013; Bui et al., 2020; Hassanzahed et al., 2020) Our results corroborate these findings and suggest that the sta-tistical association between driving behavior and crash outcomes may
be related to risky driving behavior while transporting goods For example, drinking while driving is strongly associated with risky driving behavior (Faried et al., 2017; Nguyen et al., 2013; Vu et al., 2020) In this study, this factor was positively associated with major crashes Smoking and mobile phone use while driving are also likely to increase rider inattention and therefore increase the incidence of crashes (La
et al., 2013; Nguyen et al., 2020; Truong et al., 2018) Interestingly, the influence of smoking while driving on the incidence of major crashes was 4.6 times higher than the influence of using a mobile phone while driving This result corroborated the findings of previous studies (Mangiaracina and Palumbo, 2007; Merrill, 2019), which showed that drivers were more distracted by smoking while driving than by using a mobile phone, and that smoking constitutes a considerable risk for road safety In this context, a traffic safety system that encourages cargo MC drivers to reduce the risk of traffic crashes by themselves is therefore
Fig 3 Opinions of drivers with different levels of crash experience regarding road safety Chi-square tests showed that none of the variables were significant
Trang 7Case Studies on Transport Policy xxx (xxxx) xxx
considered necessary Authorities from the Department of Transport
should review the driving ability and qualifications of commercial
drivers frequently to increase road safety In addition, a commercial
vehicle driver’s license system for drivers who are likely to cause traffic
crashes should be introduced If drivers cause traffic crashes frequently,
they should receive special treatment and factors such as their driving
behavior, situational awareness, risk assessment ability, personality,
should be assessed Transport authorities and logistics companies should
implement mitigation measures and educate carriers and cargo MC
drivers
Our results also showed that there was a significant negative
rela-tionship between smoking while driving and traffic crashes (Table 2 and
Fig 2) The difference in the causes of crashes between drivers that have,
and have not, experienced major crashes is interesting but not
surpris-ing It is self-evident that, even without distractions, the jobs of cargo
MC drivers are dangerous A recent study showed that truck drivers lose
10 to 12 s of attention if they use a mobile phone or smoke while driving,
which is equivalent travelling 150 or 160 m without looking at the road
(Mangiaracina and Palumbo, 2007) In the case of a using a MC, the level
of distraction is even larger Consequently, it may not be surprising that
smoking and/or using a mobile phone while driving increases the risk of
having a major crash instead of a minor crash
Competence in transporting cargo by MC is crucial The results show
that while experienced cargo MC drivers were more likely to avoid being
in a major crash, they were more likely to be involved in minor crashes
This finding is not surprising given the fact that experienced drivers are
typically confident, and they tend to carry as much as possible in order
to meet their delivery targets Overloading may have a detrimental
ef-fect on the other vehicles on the road, resulting in minor crashes in a
variety of ways Although experienced drivers can often avoid major
crashes and minimize the risk of a crash, all commercial vehicle drivers
should be trained, assessed, certified, and licensed regularly through
professional training agencies or local transport associations The cost of
training should be covered by the logistics companies as drivers are the
primary labor force of the logistics companies and are trained to benefit
these companies
7 Conclusion
The aims of this study were to examine and clarify the factors
asso-ciated with the incidence of traffic crashes and the perceived risks in a
representative sample of cargo MC drivers To the best of our
knowl-edge, this is the first such study in Vietnam It is considered that the
findings will have important implications for freight transportation and
public health planning in urban areas For example, the survey results
clearly showed that road traffic crashes are common among cargo MC
drivers These traffic crashes were primarily a consequence of fatigue
resulting from long work hours, lack of rest, and workplace pressure In
addition, poor driving behavior and lack of experience were also
generally responsible for road traffic crashes in the LMD service sector
Crash severity differed significantly depending on influencing factors
and socio-demographics, suggesting that cargo MC drivers may present
significant challenges to urban freight transport Although cargo MCs
fulfill a niche in urban freight transportation, this niche may not
encourage healthy and sustainable shipment practices if there is a lack of
safety management plans by policymakers
There are a number of limitations to this research, the most notable
of which is related to the data used We conducted an online survey
certain details about the crashes, and details such as the time of the
crash, road type, traffic density, and severity of injures, were omitted to
avoid making the questionnaire too long Consequently, the details of
specific road traffic crashes could not be determined with absolute
certainty It is also possible that drivers’ perception of overall safety may
influence their driving behavior In fact, a recent study reported that risk
averse drivers were likely to have negative attitudes towards risky
driving behavior (Nguyen-Phuoc et al., 2020a) However, since no
information on risk perceptions or attitudes was collected in this survey, these potential influences were not examined Lastly, crash prevalence and severity were correlated with experience of a crash While the sample size was sufficiently large to produce statistically reliable results, the data were not longitudinal; in other words, we did not examine the changes in road traffic crashes over time
Despite these limitations, the findings of this study have important implications for policy and practice Recent improvements in road infrastructure may not be very effective in reducing urban road traffic accidents, particularly in the urban freight transportation sector Instead, programs and initiatives for commercial vehicles should focus
on aptitude testing and safe driving education for drivers of commercial vehicles, including the cargo MC drivers employed by logistics com-panies In addition, programs should be developed to better understand and reshape the culture of cargo MC drivers Based on the findings of this study, it appears that establishing a stress-free working environment, improving working conditions, and establishing safety management plans will enable logistics companies to increase the safety of their drivers, and in so doing, potentially improve drivers’ physical and psychological health and wellbeing
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper
Acknowledgements
This study is based on research supported by Vietnam Ministry of Science and Technology and German Federal Ministry of Education and Research (Project No NDT/DE/21/300 The authors are solely respon-sible for the contents of this paper
References
Baas, P., Charlton, S., Bastin, G.T., 2000 Survey on New Zealand truck driver fatigue and fitness for duty Transp Res F: Traffic Psychol Behav 3 (4), 185–193
Barua, S., El-Basyouny, K., Islam, M.T., 2014 A full Bayesian multivariate count data model of collision severity with spatial correlation Anal Methods Accid Res 3-4, 28–43
Bazargan-Hejazi, S., Zamani-Alavijeh, F., Hindman, D., Mohamadi, E., Bazargan, M.,
2013 How do motorcyclists manage mental tensions of risky riding? BMC Public Health 13 (1), 865
Bray, D.J., Holyoak, N., 2015 Motorcycles in developing Asian cities: A case study of Hanoi 37th Australasian Transport Research Forum, Sydney
Bui, H.T., Saadi, I., Cools, M., 2020 Investigating on-road crash risk and traffic offences
in Vietnam using the motorcycle rider behaviour questionaire (MRBQ) Saf Sci 130,
104868 https://doi.org/10.1016/j.ssci.2020.104868
Chu, M.C., Nguyen, L.X., Ton, T.T., Huynh, N., 2019 Assessment of motorcycle ownership, use, and potential changes due to transportation policies in Hochiminh
City, Vietnam J Transp Eng., Part A: Systems 145 (12), 05019007
Clifton, C., Burnier, C., Akar, G., 2009 Severity of injury resulting from pedestrian- vehicle crashes: What can we learn from examining the built environment? Transp Res Part D 14 (6), 425–436
Doustmohammadi, M., 2019 Urban freight crash analysis using ordinal logit and ordinal probit regression in the state of Alabama Int J Transp Eng 9 (1), 127–144
Faried, A., Bachani, A.M., Sendjaja, A.N., Hung, Y.W., Arifin, M.Z., 2017 Characteristics
of moderate and severe traumatic brain injury of motorcycle crashes in Bandung, Indonesia World Neurosurgery 100, 195–200
Fisher, D.L., Laurie, N.E., Glaser, R., Connerney, K., Pollatsek, A., Duffy, S.A., Brock, J.,
2002 Use of a Fixed-Base Driving Simulator to Evaluate the Effects of Experience and PC-Based Risk Awareness Training on Drivers’ Decisions Hum Factors 44 (2), 287–302
Freswell, R., Williamson, A., 2010 Work characteristics associated with injury among ligh/short-haul transport drivers Accid Anal Prev 42 (6), 2068–2074 Giuliano, G., O’Brien, T., Dablanc, L., Holliday, K., 2013 Synthesis of freight research in
urban transportation planning (Vol 23) Washington, DC: Transportation Research Board Available from: https://www.infrastructureusa.org/wp-content/uploads/20 13/06/ncfrp_rpt_023.pdf
Giuliano, G., Kang, S., Yuan, Q., 2018 Using proxies to describe the metropolitan freight landscape Urban Studies 55 (6), 1346–1363
Guo, F., Wang, X., Abdel-Aty, M.A., 2010 Modeling signalized intersection safety with corridor-level spatial correlations Accid Anal Prev 42 (1), 84–92
A.M Ngoc et al
Trang 8Guo, Q., Xu, P., Pei, X., Wong, S., Yao, D., 2017 The effect of road network patterns on
pedestrian safety: a zone-based Bayesian spatial modeling approach Accid Anal
Prev 99 (2017), 114–124
Hartley, L.R., Hassani, J.E., 1994 Stress, violations and accidents Appl Ergon 25 (4),
221–230
Hassanzadeh, K., Salarilak, S., Sadeghi-Bazargani, H., & Golestani, M., 2020
Motorcyclist risky riding behaviors and its predictors in an Iranian population
Journal of Injury and Violence Research, 12(2), 161 https://dx.doi.org/10.5249%
2Fjivr.vo112i2.161
La, Q.N., Lee, A.H., Meuleners, L.B., Duong, D.V., 2013 Prevalence and factors
associated with road traffic crash among taxi drivers in Hanoi, Vietnam Accid Anal
Prev 50, 451–455
Lagarde, E., Chastang, J.F., Gueguen, A., Coeuret-Pellicer, M., Chiron, M., Lafont, S.,
2004 Emotional stress and traffic accidents – The impact of separation and divorce
Epidemiology 15 (6), 762–766
Mangiaracina, G., Palumbo, L., 2007 Smoking while driving and its consequences on
road safety Annali di Igiene, 2007; 19(3):253-67 Available from: https://pubmed
ncbi.nlm.nih.gov/17658112/
McDonald, N., Yuan, Q., Naumann, R., 2019 Urban freight and road safety in the era of
e-commerce Traffic Inj Prev 20 (7), 764–770
Merrill, R.M., 2019 Injury-related deaths according to environmental, demographic and
lifestyle factors Available from J Environ Public Health 2019 (6942787) https://
pubmed.ncbi.nlm.nih.gov/30944571/
Ministry of Planning and Investment (MPI), 2021 Report on results of the
implementation of the medium-term public investment plan for the period 2016-
2020 and the expected medium-term public investment plan for the period of 2021-
2025 Government of Vietnam
National Traffic Safety Committee (NTSC), 2017 Master plan of road traffic safety in
Hanoi Final report NTSC
Ngoc, A.M., Hung, K.V., 2019 Evaluation of the effects of traffic management at school
areas Lect Notes Civ Eng 54, 1037–1042
Ngoc, A.M., Nishiuchi, H., Truong, N.V., Huyen, L.T., 2021 A comparative study on
travel mode share, emission, and safety in five Vietnamese cities Int J Intell
Transp Syst Res 20 (1), 157–169
Ngoc, A.M., Thanh, T.T.M., 2019 Policy implications from traffic accident analysis: A
study case from Vietnam Lect Notes Civ Eng 54, 1043–1048 https://doi.org/
10.1007/978-981-15-2-8_167
Ngoc, A.M., Thanh, T.T.M., 2020 Towards the development of traffic safety strategies in
developing countries: Analysis of road users’ perspective Transp Res Procedia 48,
1278–1287 https://doi.org/10.1016/j.trpro.2020.08.149
Ngoc, L.B., Thieng, N.T., Huong, N.L., 2012 The drink driving situation in Vietnam
Traffic Inj Prev 13 (2), 109–114
Nguyen, N.P., Passmore, J., Tran, L.T.N., Luong, A.M., 2013 Role of alcohol in
hospitalized road trauma in Vietnam Traffic Inj Prev 14 (4), 329–334
Nguyen, D.V.M., Ross, V., Vu, A.T., Brijs, T., Wets, G., Brijs, K., 2020 Exploring
psychological factors of mobile phone use while riding among motorcyclists in
Vietnam Transportation Research Part F: Traffic Pssychology and Behaviour 73, 292–306
Nguyen, D.V.M., Vu, A.T., Ross, V., Brijs, T., Wets, G., Brijs, K., 2021 Small-displacement motorcycle crashes and risky ridership in Vietnam: Findings from a focus group and in-depth interview survey Saf Sci https://doi.org/10.1016/j.ssci.2021.105514
Nguyen-Phuoc, D.Q., Oviedo-Trespalacios, O., Su, D.N., Gruyter, C.D., Nguyen, T., 2020a Mobile phone use among car drivers and motorcycle riders: The effect of probmatic mobile phone use, attitudes, beliefs and perceived risk Accid Anal Prev
143, 105592
Nguyen-Phuoc, D.Q., De Gruyter, C., Oviedo-Trespalacios, O., Diep Ngoc, S.u., Tran, A.T P., 2020b Turn signal use among motorcyclists and car drivers: The role of environmental characteristics, perceived risk, beliefs and lifestyle behaviours Accid Anal Prev 144, 105611
Petridou, E., Moustaki, M., 2001 Human factors in the causation of road traffic crashes Eur J Epidemiol 9 (16), 819–826
Pokorny, P., Drescher, J., Pitera, K., Jonsson, T., 2017 Accidents between freight vehicles and bicycles, with a focus on urban areas Transp Res Procedia 25, 999–1007
Schwab, J.A (2002) Multinomial logistic regression: Basic relationships and complete problems http://www.utexas.edu/courses/schwab/sw388r7/SolvingProblems/
Shope, J.T., Bingham, C.R., 2002 Driking-driving as a component of problem driving and problem behavior in young adults J Stud Alcohol 63 (1), 24–33
Thanh, T.T.M., Ngoc, A.M., 2020 Parking behavior and the possible impacts on travel alternatives in motorcycle-dominated cities Transp Res Proc 48, 3469–3485
Torregroza-Vargas, N.M., Pablo Bocarejo, J.P., Ramos-Bonilla, J.P., 2014 Fatigue and crashes: The case of freight transport in Colombia Accid Anal Prev 72 (2014), 440–448
Truong, L.T., Nguyen, H.T.T., Gruyter, C.D., 2018 Correlations between mobile phone use and other risky behaviours while riding a motorcycle Accid Anal Prev 118, 125–130
Truong, L.T., Nguyen, H.T.T., Tay, R., 2020 A random parameter logistic model of
fatigue-related motorcycle crash involvement in Hanoi Vietnam Accid Anal Prev
144, 105627 University of Transport and Communications (UTC), 2020 Traffic counting survey
report Final report UTC, 2020
Vu, A.T., Nguyen, M.T., Nguyen, D.V.M., Khuat, V.H., 2020 Investigating the effect of blood alcohol concentration on motorcyclist’s riding performance using an advanced motorcycle simulator Transp Res F: Traffic Psychol Behav 73, 1–14
Williams, A.S., O’Neill, B., 1974 On the road driving records of licensed race drivers Accid Anal Prev 72, 260–272
Further reading
Ziakopoulos, A., Yannis, G., 2020 A review of spatial approaches in road safety Accid Anal Prev 135, 105323