An empirical analysis of freight mode choice factors amid the COVID-19 outbreak
| DOI | https://doi.org/10.1108/IMDS-03-2022-0133 |
| Published date | 30 September 2022 |
| Date | 30 September 2022 |
| Pages | 2783-2805 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Vipulesh Shardeo,Jitender Madaan,Felix T.S. Chan |
An empirical analysis of freight
mode choice factors amid
the COVID-19 outbreak
Vipulesh Shardeo
Lal Bahadur Shastri Institute of Management Delhi,
New Delhi, India
Jitender Madaan
Indian Institute of Technology Delhi, New Delhi, India, and
Felix T.S. Chan
Department of Decision Sciences, Macau University of Science and Technology,
Macau, China
Abstract
Purpose –The COVID-19 has affected the whole world and forced countries to impose lockdowns and restrict
travel and transportation. This was followed by different countries formulating different policies, and when
transportation resumed, there were some restrictions. Such strategies forced transporters to rethink mode
choice decision making for freight transportation. The purpose of this study is to identify and rank the factors
affecting freight transport mode choice decisions considering the spread of COVID-19 outbreak.
Design/methodology/approach –Initially, the factors affecting the mode choice decisions for freight
transportationamid the COVID-19 outbreak have been extracted from a literature survey and group discussion
with experts. Further, this paper employs the integration of grey-Decision making trial and evaluation
laboratory (DEMATEL) with fuzzy Best Worst Method to analyze the identified factors and their sub-factors.
The model’s robustness and feasibility were then tested using sensitivity analysis.
Findings –The findingsof the study showedthat Disaster Characteristicsand Operations Factorsare the most
and least influential factors,respectively. Panic,Travel restrictions, Border restrictions, Severity,and Mortality
rate are the top five ranked sub-factors. Panic, Compliance to Social distancing, and Passenger and Freight
integrationare among the new sub-factors proposed.In the current circumstances, thesesub-factors are crucial
and relevant. In addition, various recommendations are offered to improve transportation services while
guaranteeing safety, such aspromoting passenger and freight integration, lowering thepanic level, developing
dynamic rules based on region characteristics, and so on. The study’s findings will help practitioners and
politiciansreformulate the existing transportation infrastructure in the eventof disease outbreaks.
Research limitations/implications –The demographic contextof experts, is one of the study’s limitations.
Only experts from the Indian subcontinent were considered in this study. In addition,future study work can be
based on a comparison of the outcomes from various Multi-Criteria Decision Making techniques.
Originality/value –The present research work differentiates itself through the analysis of mode choice
factors considering the ongoing pandemic across the globe. The results emanated from the study can guide the
concerned stakeholders to make better decisions.
Keywords Freight transportation, Mode choice, COVID-19, Grey theory, DEMATEL, BWM, Fuzzy
Paper type Research paper
1. Introduction
All types of global crises in all sectors have a significant impact on a nation’seconomyandhalt
commercial activities. Epidemics and disease outbreaks are the most detrimental to human health
and have the greatest impact. This results in a significant loss for developingnations such as India,
which are highly dependent on manpower. Over the last century, the major epidemics were the
Analysis of
freight mode
choice factors
2783
The authors would like to thank the members of Research Committee of Indian Institute of Technology
for technical support.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 3 March 2022
Revised 7 July 2022
30 August 2022
Accepted 14 September 2022
Industrial Management & Data
Systems
Vol. 122 No. 12, 2022
pp. 2783-2805
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-03-2022-0133
Spanish Flu (1920), SARS (2000) and Swine Flu (2009), which killed millions of people and
weakened the economies (Qiu et al., 2017).Asimilarworldwideepidemiciswitnessedtoday,
referred to as Coronavirus or COVID-19, which has taken around 5.98 million lives till March 2,
2022 (Worldometer, 2022). The virus first appeared in late 2019 in Wuhan City, China and then
spread over the world within a short period. Later, World Health Organization declared COVID-19
a worldwide pandemic in March 2020 (WHO, 2020). The pandemic wreaked havoc on nearly every
industry and precipitously increased the demand for medical supplies. People initially panicked,
leading to the hoarding of food supplies. To combat the spread of the deadly disease, governments
in various nations enacted measures including travel restrictions, lockdowns, social isolation, etc
(Zhao et al.,2021). These actions halted the whole supply chain and caused massive loss to the
transportation sector (Loske, 2020). Because it also involves the movement of essential goods such
as medical supplies, food, etc., freight transport cannot be completely restricted. Consequently,
transportation for essential services such as medical supplies, food products, etc., continued even
during the peak of the virus spread.
The unprecedented pandemic caused a surge in demand for medical supplies such as personal
protective equipment (PPE) kit, masks, sanitizers, etc. China started manufacturing these medical
suppliesatthestartoftheCOVID-19spread. Before the announcement of COVID-19 as a
pandemic, China produced around 20 million medical masks per day, which accounted for almost
50% of the world’s supply (Bouali et al., 2020). With the rapid spread of the deadly virus, affected
countries such as Italy, Spain and the United States needed medical supplies from China and other
manufacturing hubs as fast as possible. Faster delivery of supplies can be possible through air
mode of transportation. The decline in passenger transportation due to border closures and travel
restrictions increased the cost of air cargo and led to substantial transportation costs. As a
repercussion of the pandemic, the air transport segment is seriously affected. Regarding railways,
especially in India, a rise in freight demand has been witnessed. The transportation of medical
supplies and food products accounts for the major share. Although the least affected mode of
transportation is by road compared to other modes like airways and waterways (Marquez and
Tolosa, 2020). This led to road transport as the most demanding and critical mode during the
pandemic. However, the threat of virus exposure is still a vital issue that results in a shortage of
truck drivers. The reason is obvious that the life of people involved in the transportation sector
cannot be put at risk due to the deadly spread of COVID-19 (Lau et al., 2021).
In addition to this, after few days, considering the severity of the COVID-19 outbreak,
different countries opened transportation services gradually. Despite the fact that some
countriesloosenedrestrictions,the panic and healthcrises caused workforceissues fortransport
companies.Consequently, such actions have a significant impacton the economy, particularly
for developing nationslike India. Thesecomplexities in transportservices compelled concerned
stakeholders to reconsider mode selection decisions from a new angle. Consequently, the
decision-making process must be reformulated considering the COVI D-19 outbreak.
This became a new requirement, so the purpose of this paper is to address the resulting void.
The main objective of this study is to investigate the factors affecting mode choice decision
considering the COVID-19 outbreak. The study is conducted in three phases. First, the factors and
sub-factors are extracted from the literature and discussed with a panel of experts. Second, the
identified factors and their sub-factors are validated by a panel of experts, and then key factors are
assessed to present a cause-effect relationship and obtain the priority weights. Third, the sub-
factors are prioritized by obtaining the local and global weights. Regarding main contribution, the
present study proposed an integrated methodology that would allow decision-makers to select
modes under uncertain conditions.Prior research has integrated the various techniques for MCDM
problems. As far as the authors are aware, this paper is uniquely contributed to the context of a
freight mode choice problem by combining grey DEMATEL and fuzzy BWM. The remainder of
this paper is as follows: Section 2 presents the relevant literature survey; Section 3 describes the
IMDS
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