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Mapping the key challenges and
managing the opportunities in
supply chain distribution during
COVID-19: a case of Myanmar
pharmaceutical company
Vimal Kumar
Supply chain
distribution
during
COVID-19
Received 10 January 2022
Revised 26 February 2022
Accepted 13 April 2022
Department of Information Management, Chaoyang University of Technology,
Taichung, Taiwan, and
Kyaw Zay Ya and Kuei-Kuei Lai
Department of Business Administration, Chaoyang University of Technology,
Taichung, Taiwan
Abstract
Purpose – This study aims to present a study on the supply chain process of a Myanmar-based
pharmaceutical company (named ABC Pvt. Ltd. in this study) that produces pharmaceutical products across
Myanmar and aims of bringing quality medical products and best care for Myanmar people’s health. The
study aims to identify the key supply chain challenges and manage the opportunities executed by this
pharmaceutical company to improve the supply chain process during the COVID-19 outbreak.
Design/methodology/approach – This work used a case study and conducted semistructured
interviews with the manager, senior managers and senior staff of the ABC Company to improve the supply
chain process and develop a comprehensive structural relationship to rank them to streamline the
uncertainties, real-time information and agility in a digital supply chain using grey relational analysis (GRA)
method.
Findings – From the data analysis and results, “Impact of political factor,” “Delay in import process” and
“Weak internet connection,” and “Weak knowledge of the use of digital platform,” “Poor information sharing
in online by employees” and “Information flow from top management to operational level” have been
identified as top and bottom three key challenges, respectively. “Inventory management,” “Selection of
transport method” and “Operational cost”, and “Marketing and brand Innovation,” “Online delivery of
products” and “E-commerce enablement (Launching applications, tracking system)” are identified as the top
and bottom three managing the opportunities, respectively.
Research limitations/implications – The findings of the study help to supply chain decision-makers
of the company in their establishment of key challenges and opportunities during the COVID-19 era. As a
leading company, it always tries to add value to its product through a supply chain system, effective
management teams and working with skillful decision-making toward satisfying the demand on time and
monitoring the supplier performance.
The authors would like to thank the two anonymous reviewers, Associate Editor, and Editor-in-Chief
for their valuable comments and suggestions that helped to improve the manuscript.
Funding: The authors received no financial support for the research, authorship and/or
publication of this article.
Declaration of conflicting interests: The authors declared no potential conflicts of interest with
respect to the research, authorship and/or publication of this article.
Journal of Global Operations and
Strategic Sourcing
© Emerald Publishing Limited
2398-5364
DOI 10.1108/JGOSS-01-2022-0002
JGOSS
Originality/value – The novelty of this study is to identify the key supply chain challenges and
opportunities by the GRA method to rank them, considering the case of Myanmar pharmaceutical
manufacturing company as a case-based approach to measuring its performance during the COVID-19
outbreak era. This work will assist managers and practitioners help to the company to provide optimal
services to its consumers on time in this critical situation.
Keywords Supply chain distribution, Pharmaceutical company, Challenges, Opportunities,
COVID-19, GRA method
Paper type Research paper
1. Introduction
The COVID-19 pandemic has forced us to rethink our health-care systems, business models,
lifestyles and many other things, including supply chain management (Singh et al., 2022;
Bag et al., 2021b). Nowadays, the global supply chains (SC) have been badly affected by a
wide-ranging pandemic COVID-19 virus (Mayounga, 2021; Bag et al., 2021c). The outbreak
of this COVID-19 virus is the most overwhelming disturbance and has hugely impacted
global economic activities like manufacturing operations, SC and logistics and several
others (Goel et al., 2021; Nikolopoulos et al., 2021; Alam et al., 2021). We observed demand
and supply ripples; chaos and resonance effects propagated across global networks (Guan
et al., 2020). The various industries including different manufacturing and service sectors
are affected by the cause of this disease; these include the pharmaceuticals industry,
restaurant industry, energy industry, solar power sector, tourism, airlines, information and
electronics industry (Haleem et al., 2020; and Song et al., 2021). Many industries encountered
supply chain issues and had to manage and perform well as a result, while others, such as
pharmaceutical and technology industries, faced new challenges as well as opportunities.
According to Ayati et al. (2020), COVID-19 may be seen as a century’s opportunity for the
pharmaceutical industry; as it increases the demand for prescription medicines, vaccines and
medical devices. This industry has short- and long-term effects. Demand change, supply
shortages, panic buying and stocking, regulation changes can be seen as short-term impacts of
COVID-19 on the health market; while approval delays, moving toward self-sufficiency in the
pharm-production supply chain, industry growth slow-down and possible trend changes in
consumption could be seen as long-term impacts of COVID-19 on the health and pharmaceutical
market (Ayati et al., 2020). Several challenges were observed in the pharmaceutical industry’s
management of the pandemic, including difficulty meeting the demand for protective gear and
diagnostic testing facilities (Almurisi et al., 2020; Peeri et al., 2020). Likely to various other
companies, pharmaceutical companies are also bound to manufacture and distribute their
medicines and products on time. Every country in the world is facing supply chain challenges
like demand pattern, expenses, inventory management and customer response. In this study, our
target was to see the challenges and opportunities of Myanmar’s pharmaceutical companies.
According to Htut (2022), Myanmar is upgrading the health-care industry in the past decade by
increasing government spending on its medical services spending plan. Despite the fact that
Myanmar’s pharmaceutical expenditure has climbed at a rate of 13%–14% per year, from US
$391m in 2015 to US$409m in 2016 (World Health Statistics Report, 2021; Myanmar Health
Statistics Report, 2020). However, the nation is still experiencing a variety of obstacles and
challenges during COVID-19, such as inventory, availability of raw materials from the supplier
side, human resource (HR) and customer management concerns such as out of stock, supply to
match demand, inventory holding costs and credit management. In this current COVID-19 crisis,
the pharmaceutical industry supply chain can be scaled up quickly and flexibly to save lives
(Hsiao et al., 2020). As a result, during the COVID-19 epidemic, SC were more tightly compressed
to manage the process and control the upstream and downstream flows of supplies on time
(Handfield et al., 2020). Transportation facilities were severely impacted, but all small and large
pharmacies/stores simply ran out of stock during COVID-19 due to a constrained supply system
for raw materials and manufacturing, as well as panic buying among customers (Uwizeyimana
et al., 2021). Therefore, we focus to see these distribution challenges of this Myanmar-based
pharmaceutical company and try to manage the opportunities. For this, we derive the research
questions and research objective after that. The study objectives are to foster the identification
and prioritizing to smooth out the supply chain process and ensure timely distribution. With the
aforementioned factors in mind, this study concentrated on the following research questions:
RQ1. What are the essential key supply chain challenges and opportunities in a Myanmarbased pharmaceutical manufacturing company during the COVID-19 era?
RQ2. What method of preference ranking was used to organize them to manage and to
improve the supply chain performance?
The study proposed the following objectives:
Identifying the key challenges and opportunities for a pharmaceutical
manufacturing company’s supply chain during the COVID-19 outbreak.
Prioritizing the identified key challenges and opportunities using the grey relational
analysis (GRA) approach.
For the purpose of investigation, we adopted the multi-criteria decision making (MCDM)
technique for final data analysis. Under the MCDM techniques, we performed the GRA method.
The structure of this paper is divided into the following sections. The detailed literature
review is presented revolving around the COVID-19 outbreak, focused on different key
supply chain challenges and managing the opportunities of a pharmaceutical
manufacturing company in Section 2. Section 3 outlines the research methodology followed
by data analysis and results in Section 4. The discussions and findings with theoretical and
managerial implications are explained in Section 5, followed by the conclusions with
limitations and future scope in Section 6.
2. Literature review
2.1 COVID-19 and supply chain in pharmaceutical company
In today’s dynamic and globalized world, producing a product or service involves a complex
network of buyer-supplier links, not just the corporation (Jha et al., 2022; Jensen, 2017). Many
governments throughout the world have attempted to guarantee an appropriate supply of
key pharmaceuticals by limiting exports in reaction to the increased possibility of public
health problems as a result of the COVID-19 epidemic (Piatek et al., 2020). This crisis has
caused supply chain issues, but it has also caused widespread upheaval in the corporate
world, affecting everyone from small to large firms (Alhawari et al., 2021). The
pharmaceutical industry supply chain can be scaled up swiftly and flexibly to save lives in
this current COVID-19 crisis (Hsiao et al., 2020). The good relation among all supply chain
partners to manufacture and distribute on time. Especially, the pharmaceutical companies
are bound to manufacture and distribute their medicines and products on time. In any
circumstances, the SC are more tightly compressed to manage the process and control the
upstream and downstream flows of materials during the COVID-19 outbreak (Handfield
et al., 2020). The use of digital tools for seamless communication, together with substantial
developments in pharmaceutical manufacture and delivery (Sarkis et al., 2021). But all small
and big pharmacies/stores just ran out of stock during COVID-19 because of the limited
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supply system of raw materials and manufacture and the panic buying practice among the
customers (Uwizeyimana et al., 2021). Data analytics in pharmaceutical SC has sparked a lot of
attention in recent years because it has the potential to improve health-care product supply and
management by harnessing data provided by current technologies (Nguyen et al., 2021; Bag et al.,
2021b; Kaupa and Naude, 2021). But the pharmaceutical companies face different key supply
chain challenges and the need to manage the opportunities to provide optimal services to their
customers. In this situation, the businesses must concentrate on seeking continuous improvement
in production efficiency and effectiveness of manufacturing operations and distribution (Verma
et al., 2021; Chowdary and George, 2012).
The pharmaceutical market is taken into consideration as a major perspective in the healthcare sector (Nasrollahi and Razmi, 2019; Singh et al., 2016) and it can be stated that its significant
contribution to society has been doubled during the COVID-19 outbreak. The current situation is
still pandemic time (WHO, 2021), and the UK has restarted lockdown rules recently due to such a
rage spread of the new COVID variant, Omicron (The Guardian, 2021). COVID-19 disrupts the
world of work and reshuffles the outlook of factories (Ramanathan et al., 2021; Khan et al., 2021;
Al-Mansour and Al-Ajmi, 2020; Akintokunbo and Adim, 2020). It has lengthened the supply
chain resilience to the limited margin by assessing the agility and flexibility of the supply chain in
the enterprises including pharmaceutical business (Handfield et al., 2020; Sarma et al., 2021;
Karmaker and Ahmed, 2020; Piprani et al., 2020; Ivanov, 2020). However, the firms have figured
out how to improve the resilience of their global SC in the face of severe calamities (Ivanov and
Das, 2020; Modgil et al., 2021). It has changed typical work-related mobility to digital work
(Taylor and Taylor, 2021). Digital evolution has caused local and international pressures on
typical business leaders through many restrictions (Ivanov and Dolgui, 2021; Ahmad and John,
2021; Parmata and Chetla, 2021). However, it provides several advantages to supply chain
players such as reducing work processing time, faster online tracking, quick information sharing
and order forecast (Mishra et al., 2021; Pyun and Rha, 2021). As the results of that existing
literature indicate the effects of COVID-19 spread and regulatory rules are significantly testing
the use of business strategies under uncertainties, real-time information and supply chain agility
of pharmaceutical companies.
2.2 Uncertainties
The pharmaceutical factory is a kind of industry that is full of challenges related to uncertainties
in the world (Schumacher et al., 2020). Among three types of uncertainty related to sustainable
supply chain; task uncertainty, source uncertainty and supply chain uncertainty (Busse et al.,
2017; Jauhar et al., 2021; Pathak et al., 2020; Verma et al., 2020), the challenges happening in this
sector are both probabilistic and deterministic (Tripathi et al., 2019). The demand for medicine
supply is uncertain because it can be influenced by seasonal changes, and the costs for medical
products can be uncertain due to the regulatory rules (Franco and Alfonso-Lizarazo, 2020). One of
the effects of COVID-19 is serious delay not only in production but also in the import and export
process (Butt, 2021; Kumar et al., 2022). Excessive disruption and delay in the supply chain can
increase the rate of mortality and morbidity of the patients (Ahmad and John, 2021), and supply
chain disruption may impact tremendously on business performance and its capacity to survive
(Carbonara and Pellegrino, 2018; Abdolazimi et al., 2021). Singh et al. (2016) also urged the facts
related to uncertainty, such as everchanging trends of product innovation, the short life cycle of
the product, continuous technology improvement, competitive global business market, high
production cost and time-consuming clinical trials for product development. The severer the
inventory shortage locally and internationally, the more cautious the governments and business
leaders are Schumacher et al. (2020). Such uncertainties can lead to problems in storage and
warehouse space (Agyabeng-Mensah et al., 2020). Therefore, decision-making in uncertain
conditions is a complex issue evolving a variety of functions of information sources throughout
the supply chain (Kumar et al., 2021).
2.3 Real-time information
As the supply chain has material flow and information flow, information sharing is
considered as an effective tool for facilitating the supply chain responsiveness, and it is a
forerunner which goes first before material flow (Harrison et al., 2014). However, the
importance of real-time information seems to have been ignored because it is very scanty
literature while there are many research studies related to supply chain challenges and
performances during a pandemic. Information is flowing from and to upstream and
downstream while the material is going from upstream to downstream only (Porter, 1985).
Information analysis is also considered a critical success factor in total quality management
(Duggirala et al., 2008) as cited in Kumar and Sharma (2017). Supply chain performance
from raw material through manufacturing, warehousing and distribution until the end user
can effectively be performed through information access and information technologies
(Mukhsina et al., 2021; Pansare et al., 2021; Agyabeng-Mensah et al., 2020; Tripathi et al.,
2019; Kumar et al., 2017). Right time distribution is one of the factors to fulfill customer
satisfaction and prioritizing request (Ershadi and Ershadi, 2021). The use of environmentalfriendly technologies and green packaging can also lead to customer satisfaction
(Agyabeng-Mensah et al., 2020; Bag et al., 2020a; Nantee and Sureeyatanapas, 2021). During
a pandemic, some factories are trying to boost the existing supply chain by raising
manufacturing and distribution abilities (Park et al., 2020). Enhancing distribution efficiency
through financial metrics, effective cost reduction can be performed through various stages
in the supply chain (Shah and Sing, 2001 as cited in Tripathi et al., 2019). This can help
product pricing, which has become a major challenge during the COVID-19 outbreak
(Ershadi and Ershadi, 2021) because demand uncertainty, performances of competitors,
governmental actions, bargaining power of suppliers cause high product pricing (Porter,
1985 as cited in Singh et al., 2016). As the consequence, the scholars indicate real-time
information can be concerned as a crucial role for product distribution, production process,
supply chain agility, etc.
2.4 Agility
In an agile supply chain, factors such as quality, velocity, flexibility and responsiveness
throughout the supply chain are major abilities for customer demand and market needs
(Singh et al., 2019; Mehralian et al., 2015). However, during a pandemic, it is very difficult to
ensure an adequate amount of stock to promise the capability and to perform for meeting the
business promises (Butt, 2021). Pandemic has forced the local authorized people to prohibit
imports with several regulations, and this also causes their struggle to hold a particular
number of exports (Butt, 2021). The geographical restriction is one of the factors badly
affecting business promises, supply chain agility and high logistics cost (Schumacher et al.,
2020; Ivanov, 2020; Bag et al., 2020b). The further the location between warehouse, factory
and retailers, the more consuming the cost for logistics and the more challenging it to choose
the transport methods (Agyabeng-Mensah et al., 2020). Here, sustainable logistics practices
such as the application of environmental-friendly vehicles, developing recycling processes,
low-carbon machinery or some other sustainable products can raise the company image and
brand value creation (Nantee and Sureeyatanapas, 2021; Sharma et al., 2021a; Sharma et al.,
2021b; Bag et al., 2021d; Verma et al., 2022a; Pathak et al., 2021; Saglam et al., 2020; Yadav
et al., 2020; Chauhan et al., 2020; Fratocchi and Di Stefano, 2019). On the other hand, supplier
performance and high price from the supplier side has also become the main concerns for a
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company (Jha et al., 2022; Butt, 2021; Do et al., 2020; Andersen et al., 2019) because supplier
and company are interconnected as business to business (Gupta et al., 2018). Government
tax increment also raises manufacturing costs on the supplier side (Moktadir et al., 2018).
Moreover, market fluctuation includes panic buying due to the changes in preferences for
certain commodities (Abdolazimi et al., 2021). Panic buying will go up over a period of time
because demand-supply will be low while at the same time, new merchandising by
consumers is high (Ramanathan et al., 2021). To meet the market demand, supply chain
players use several ways including postponement orientation is one of the crucial factors
through downstream, upstream and distribution for mitigating demand uncertainty (Wu
et al., 2019; Carbonara and Pellegrino, 2018; Costantino et al., 2012). Postponement is defined
as a method of locomoting one or more functions to a later spot in the supply chain
(Abdallah and Nabass, 2018). Distribution postponement is functioned by the manufacturer
to hold the stock until the order placement is confirmed (Bagchi and Gaur, 2017).
Postponement strategy seems to have been a vital role in the business supply chain during
pandemics (Wang et al., 2022; Johnson and Haug (2021). The evidence reveals that market
fluctuation during pandemics causes severe and dramatic supply chain ramifications.
2.5 Key supply chain challenges and managing the opportunities
In this competitive supply chain age between businesses, managing the challenges is a major
challenge for supply chain players and researchers (Abdolazimi et al., 2021; Franco and AlfonsoLizarazo, 2020). To manage the challenges, many researchers have explored and proposed several
means and models to help supply chain practitioners. Schumacher et al. (2020) and Sharma et al.
(2021c) suggested setting up the inspection system even in the upstream and downstream supply
chain to avoid cost-consuming backward processes and reverse logistics. In the pharmaceutical
supply chain, expired medicines can be delivered back to the manufacturing company and can be
reused (Xie and Breen, 2012, as cited in Singh et al., 2016). They also pointed out the usefulness of
agile process management because a broad-ranging supply chain with many stakeholders can
rapidly lead to constrictions in the chain. Manuj and Mentzer (2008) also discovered six strategies
for managing risks such as postponement, speculation, hedging, control/share/transfer, security
and avoidance. Ivanov and Dolgui (2020), Fierro Hernandez and Haddud (2018) and Kurniawan
et al. (2017)’s study pointed out that risk management culture positively facilitates supply chain
visibility and supplier development, a common technique in Indonesia firms on supply chain
responsiveness. Besides, Taylor and Taylor’s (2021) study indicated that advanced digital
infrastructure might be better prepared for global nations to adapt the societal disruptions such
as the COVID-19 outbreak.
Bag et al. (2021a) and Saglam et al. (2020)’s study findings showed that supply chain
responsiveness and resilience, which are risk-mitigating tactics, positively deal with supply chain
risk management (SCRM). While managing opportunities, collaboration should not be ignored,
and regarding this, Giri and Manohar’s (2021) research indicated that private blockchain-based
collaboration and public blockchain-based collaboration support behavioral intention to use. In the
collaboration phase, information flow is quite important for data transparency, real-time
information, accurate data and the use of informative technology among all stakeholders (Mishra
et al., 2021; Nantee and Sureeyatanapas, 2021; Abdallah and Nabass, 2018; Haque and Islam, 2018).
Since the supply chain is a series of activities evolving many stakeholders from operational level to
top management, effective human resource management can derive its organization to become
more ambitious and valuable in their market to provide revenue prosperity and social benefits for
their stakeholders (Anlesinya and Susomrith, 2020). However, pandemic creates HR bundles, e.g.
payroll and thus, the company applies some HR strategies such as deferment of salary increment,
nonpayment leave and temporary pay reduction (Adikaram et al., 2021; Verma et al., 2022b).
Many scholars have revealed such a surge of COVID-19 outbreaks in the government
sector. Respective governments are also struggling in handling the COVID-19 rules and
regulations (Jamaani, 2021). This study’s research location is Myanmar which has been
experienced more than 70 years of civil war (Quah, 2016) added by the COVID-19 outbreak
and military coup in 2021. Although the nation’s economy, education, health-care sectors
were calm and can well be handled by a democratic civilian government before the military
coup in February 2021, all these sectors were seemed to have interrupted, destroyed and
some are being stopped due to the military coup (VOA, 2021). In this situation, threatened by
a terrible national economy, business enterprises are trying to survive in their way.
Although Myanmar’s business field has many restrictions especially trade, import process
and customs, most of the businesses are using cloud services for their digital work during
pandemics (Oxford Business Group, 2020). However, after a military coup, the country has
been beaten hardly by a wrecking cash shortage, money inflation, increase of internet
service charges and so on (Deutsche, 2021). All enterprises including pharmaceutical
enterprises suffer such a volume of difficulties in sales, import process, customs clearance,
transportation, lockdown, employee health concern and brand innovation as well. The study
investigates the challenges being faced in Myanmar pharmaceutical product distribution
companies and strategies being applied by business players in that company for mitigating
or solving challenges through the three supply chain dominants; uncertainty, real-time
information and agility.
To clarify the actual research scope of the study, several research gaps has been
identified after the review of available literature to the concern of supply chain distribution
with supplier performance and its challenges and opportunities of Myanmar-based
pharmaceutical company during the COVID-19 outbreak. The following points emphasize
and highlight the research gaps derived from the literature review:
COVID-19 disrupts the world of work and reshuffles the outlook of factories
(Ramanathan et al., 2021; Khan et al., 2021; Al-Mansour and Al-Ajmi, 2020;
Akintokunbo and Adim, 2020). Hence, it affects the serious delay not only in
production but also in the import and export process (Butt, 2021). It is noted that
production and distribution should be maintained and managed.
Finding the way of transport between warehouse, factory and retailers are not so
easy for logistics and the more challenging to provide essential things (like
medicines) on time and conveniently (Agyabeng-Mensah et al., 2020). In the case of
Myanmar-pharmaceutical companies, getting away from these problems and
managing the opportunities is seen as a priority.
The pharmaceutical industry supply chain can be scaled up swiftly and flexibly to
save lives in this current COVID-19 crisis (Hsiao et al., 2020). Hence, the SC are more
tightly compressed to manage the process and control the upstream and
downstream flows of materials on time during the COVID-19 outbreak (Handfield
et al., 2020). The transportation facilities were affected badly, but all small and big
pharmacies/stores just ran out of stock during COVID-19 because of the limited
supply system of raw materials and manufacture and the panic buying practice
among the customers (Uwizeyimana et al., 2021).
To sum up, this study was intended to fill gaps regarding the key supply chain
challenges and manage the opportunities executed by this pharmaceutical company
to improve the supply chain process during the COVID-19 outbreak and to establish
its rank using the GRA technique in the literature.
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3. Research methodology
3.1 The case study
The Myanmar-based company ABC founded in 1993, is a company that distributes
pharmaceutical products across Myanmar with the aim of bringing quality medical
products and best care for Myanmar people’s health. With sustainable development, the
company has become one of the leading pharmaceutical distribution companies in Myanmar
by striving to cater to a local market with quality medical products. More than 27 years of
good reputation in the Myanmar medical market has proved that the company has been
developed on a concrete foundation of business performance of modern sales and sound
marketing strategies.
Its head office is located in Yangon city, business city of Myanmar, and other major
branch offices are in Mandalay city, Pyae city, Mawlamyaing city, etc. The performance and
sales targets are generally and continually analyzed to provide optimal services to its
consumers. As a leading enterprise, it owns an effective logistics and supply chain
management system starting from suppliers through warehousing, transportation and
distribution until the end consumers plus building a good relationship with its dealers,
hospitals and customers around the country.
Its upstream supply chain strategy is to deal with dealers directly and thus, its sales and
marketing employees travel to the whole nation monthly for regular and better relationship
building with dealers (Yildiz Çankaya, 2020). Besides, it also usually participates in
community activities especially medical seminars and conferences as the main sponsor.
During the COVID-19 pandemic, it also suffers negative effects on its marketing and
brand innovation, sales, supply chain system, operational cost, inventory management, etc.
Moreover, the very complicated political conflicts of Myanmar also cause additional heavy
pressures on its standing out in the business field. Ever-changing economic rules and
regulations by authorized people cause lots of delays in the product import process, customs
clearance process, geographical restrictions of logistics and so on because it is a distribution
company and most of their products are imported from foreign countries, especially Asian
countries. Besides, Asian countries are also suffering side effects of the COVID-19 outbreak
and facing a huge number of struggles in production. Thus, these two factors, the COVID-19
outbreak and Myanmar’s political instability have doubled problems, interruptions,
challenges and difficulties for the ABC Pvt. Ltd. company.
To overcome these challenges and to reduce the COVID-19 pandemic, the decisionmakers (DMs) of ABC Pvt. Ltd. have decided to identify them and propose and develop
opportunities to manage the supply chain operations. The seminal paper of Eisenhardt
(1989) has inspired and encouraged researchers to investigate a wide range of topics to
develop concepts and theories based on case studies (on various challenges and
opportunities of the pharmaceutical company supply chain). To explore and prioritize them,
a multicriteria decision-making methodology has been used in this work. This work focuses
on qualitative and quantitative methodologies based on semistructured interviews, and
observational methods are used in the Myanmar pharmaceutical company. At the beginning
of this process, we identified some challenges and opportunities and formulated a set of
questions to get the perspectives of various levels of target responders from the top
management of the company. The 11 professionals from the various department such as
logistics, audit, accounting, human resource and business division are among those who
contributed passionately. These responders have good experience and are also pioneers in
their company. The demographic details of the respondents are summarized in Table 1.
We identified 11 DMs among the respondents following the collection of responses. From
the current literature and semistructural interview, a total of 20 key challenges and twenty
Profile
Classification
Gender
Male
Female
21–30
31–40
41–50
Above 50
Manager
Supervisor
Senior Manager
Executive
Diploma
Bachelors
Post Graduate
Managerial
Technical
1–5 years
6–10 years
11–15 years
16 and above years
1–5 years
6–10 years
11–15 years
16 and above years
Warehouse
Logistics
Audit
Accounting
Human Resource
Business Division
Age
Designation
Education
Current Job Position
Current Organization Tenure
Overall Work Experience
Department of Respondents
Count
4
7
4
6
1
0
6
4
1
0
1
8
2
9
2
7
2
1
1
0
4
3
3
2
2
1
2
2
2
opportunities are identified, shown in Table 2. The flowchart of the current study’s suggested
research effort is shown in Figure 1. The questionnaire has been designed in Appendix.
3.2 Grey relational analysis method
In the grey system theory, “grey” refers to primitive data with poor, incomplete and
uncertain information, and the “grey relation” is the incomplete information relation among
these data (Chatterjee and Chakraborty, 2014). GRA technique is suitable for resolving
problems involving complex interrelationships between many components and variables
(Kuo et al., 2008; Tosun, 2006) called multiple characteristics and criteria and determining
grey relational grades (Chan and Tong, 2007; Zeng et al., 2007). Hamzaçebi and Pekkaya
(2011) define a grey relational generation as the calculation of grey relational coefficients to
address uncertain systematic issues with only partially available information. The GRA
approach is frequently used, implemented and computed to choose and rank performance
alternatives rather than relying on expert judgment. In recent studies, Yi et al. (2021) used
GRA to assess the sustainability of 15 Chinese subprovincial cities to promote sustainable
development, while Niu et al. (2021) used GRA in a Taguchi-based methodology to optimize
air-jet supply. Most MCDM approaches involve generating multidimensions of selected
criteria to one dimension of alternative and considering multiple dimensions of criteria with
multidimensions of alternatives to determine their quality and solve various selection
Supply chain
distribution
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COVID-19
Table 1.
Demographic details
of the respondents
Agility
Real-time information
Storage problem (C1)
Uncertainty
Excessive disruption and delay in inventory storage may longer
store the stock in warehouse. This may lead to storage problem
Geographical restrictions due to COVID-19 outbreak cause serious
delay in import process
Distribution postponement is performed by the product producer
to control the inventory until the order is confirmed
Pandemic prohibits tend to concern of supplier performance
Government tax increase and high price from supplier side lead to
rise the product pricing
Panic buying is caused by an anxious mindset
Descriptions
Agyabeng-Mensah et al.
(2020), Butt (2021),
Costantino et al. (2012),
Wu et al. (2019),
Carbonara and Pellegrino
(2018), Bagchi and Gaur
(2017), Gupta et al. (2018),
Abdolazimi et al. (2021)
Sources
(continued)
During pandemic, typical workplace has been changed to online
workplace. Some employees are struggle in that condition due to
the lack of technical knowledge of digital software and application
Impact of political factor (C8)
Myanmar’s political instability influence, interrupts and destroys
supply chain process
Poor information sharing in online by
Some employees hesitate for quick information sharing
Mishra et al. (2021), Pyun
employees (C9)
and Rha (2021), Nantee
and Sureeyatanapas
Weak knowledge of the use of digital
Some employees have poor technical skill of the use of software
(2021), Abdallah and
platform (C10)
and app
Information flow from top management Information access is very crucial for data transparency, real-time Nabass (2018), Deutsche
(2021)
to operational level (C11)
information and accurate data among all stakeholders
Weak internet connection (C12)
Political instability causes the increase of internet bill charges in
Myanmar
Prioritizing requests (C13)
Due to the COVID-19 outbreak, volume of order is received from
Ershadi and Ershadi
many customers. Systematic order request priority can fulfill
(2021), Agyabeng-Mensah
customer satisfaction
et al. (2020), Nantee and
Customer satisfaction on business
Punctual distribution, meeting demand, the use of environmental- Sureeyatanapas (2021),
Singh et al. (2016),
promises (C14)
friendly technologies and green packaging can also lead to
Adikaram et al. (2021),
customer satisfaction
Product pricing (C15)
Demand uncertainty, performances of competitors, governmental Schumacher et al. (2020),
actions, bargaining power of suppliers cause high product pricing Park et al. (2020)
Surging demand exacerbated by panic
buying and excessive stockpiling (C6)
Difficulties in transition from face-toface work type to digital work (C7)
Suppliers’ performance concerns (C4)
Higher cost from supplier side (C5)
Demand postponement (C3)
Delay in import process (C2)
Challenges
Table 2.
Relevant literature
review
Indicator
JGOSS
Indicator
Uncertainties
Indicator
Due to COVID-19 infection to employees, operational disruption
occurs
Pandemic creates HR bundles, e.g. payroll, and thus, company
applies some HR strategies such as deferment of salary
increasement, nonpayment leave and temporary pay reduction
Geographical restriction is a factor negatively impacting on
business promises, supply chain agility and high logistics cost
COVID-19’s new variant Omicron is currently emerging around
the world, and on the other hand, businesses have got covid
experiences since 2020. Using these experiences, it is a crucial
thing to build future plans
During pandemic, some businesses boost up existing supply chain
by raising manufacturing and distribution abilities
Descriptions
Due to pandemic and geographical restrictions, it is challenging to
select transport method based on high price, time allowance and
mode of method
High demand tends to high order frequency
Due to high demand, number of clients might increase in
pharmaceutical market
Risk management culture positively facilitates to supply chain
visibility and supplier development
As a pharmaceutical company, inventory management plays a
vital role
The severer the inventory shortage, the more cautious the
governments and business leaders
High price from supplier and other costs evolving logistics lead to
increase high operational cost
Company has to work under the policy enacted by authorized
people
Operational disruption due to COVID
infection to employees (C16)
Salary of employee (C17)
Regulatory frameworks and policies
(MO7)
Operational cost (MO6)
Inventory management (MO5)
Planning and risk management (MO4)
Client’s orders frequency (MO2)
Client’s quantity (MO3)
Managing opportunities
Selection of transport method (MO1)
Punctual distribution (C20)
Geographical restriction on logistical
flow (C18)
Perspective on future plan while
emerging new COVID Omicron variant
(C19)
Descriptions
Challenges
(continued)
Sources
Agyabeng-Mensah et al.
(2020), Kurniawan et al.
(2017), Schumacher et al.
(2020), Franco and
Alfonso-Lizarazo (2020)
Sources
Supply chain
distribution
during
COVID-19
Table 2.
The use of pandemic experience for
business development (MO20)
Reverse logistics (MO19)
Company-supplier-customer
relationship management (MO14)
Marketing and brand innovation
(MO15)
Effective utilization of human and
equipment (MO16)
Online delivery of products (MO17)
E-commerce enablement (MO18)
The ability to meet promised delivery
date (MO8)
Integration/collaboration of activities
across the supply chain through realtime information sharing (MO9)
Providing information in a timely
manner (MO10)
Providing the training for the use of
digital apps and software for on time
information (MO11)
Adoption of new technologies that can
help distributors provide real-time
updates (MO12)
Support service (MO13)
Information
Agility
Challenges
Table 2.
Indicator
This is a branch of distribution channel to use online couriers
During pandemic, companies require to procure new e-commerce
software or app to facilitate work process
In pharmaceutical supply chain, expired medicines can be sent
back to factory and can be reused
Pandemic has entered into almost two years. Business enterprises
have got pandemic experiences which can be used for future
business development
To enhance employees’ skills, additional training is needed to be
provided
Relationship management is an essential tool among suppliers,
customers and company
Brand innovation is considered as a
During pandemic, enterprises adopt to survive in a competitive
market, e.g. Zoom application
Some employees possess poor technical skills of using digital
applications. Thus, additional is provided
Information transparency and quickness help to meet business
promises
In collaboration phase, information flow is quite important for
data transparency, real-time information, accurate data and the
use of informative technology among all stakeholder (
Real-time information resides the core of material supply chain
Descriptions
Giri and Manohar (2021),
Singh et al. (2016)
Pyun and Rha (2021),
Mishra et al. (2021),
Nantee and
Sureeyatanapas (2021),
Abdallah and Nabass
(2018)
Sources
JGOSS
Supply chain
distribution
during
COVID-19
Extensive Literature Review and Identify
the Challenges and Opportunities
Form Decision Making
Team
Determine the Criteria
No
Decision
Hesitancy
Yes
Establish a Grey Relation
Generation Matrix
Normalize the Decision
Matrix
Define the Reference Sequence
Find the Deviation Sequence
Values of Decision Matrix
Calculate the Grey
Relational Coefficient
Compute the Grey
Relational Grade
Determine the preference
Order
difficulties for this decision model. Further, it also assesses the performance of grey
relational generation, a comparative sequence. A reference sequence (ideal target
sequence) is constructed based on this sequence, and the grey relational coefficients
between all the comparability sequences and the reference sequence are then
computed. After that, the grey relational grade is calculated using these coefficients.
If a comparability sequence translated from an alternative has the highest grey
relational grade between the reference sequence and itself, that alternative is the best,
and the last is the worst. The GRA method’s procedural steps are listed below
(Chatterjee and Chakraborty, 2014; Lotfi, 1995).
3.2.1 Step 1: Grey relation generation (normalization). When the units of several
selection criteria differ, normalizing, also known as grey relational generation or data
preprocessing, is necessary to convert all of the performance values for each choice into a
comparable sequence. If there are m options and n criteria in a decision-making problem, the
ith alternative can be written as Yi = (yi1, yi2,. . ..,yij,. . .,yin), where yij is the performance
value of criterion j of alternative i. Using equation (1) or equation (2), the term Yi may
be converted into the relevant comparability sequence, Xi = (xi1, xi2,. . .,xij,. . .,xin) (2). The
Figure 1.
Flowchart of the
proposed research
work
JGOSS
decision matrix can be normalized using equation (1) if the criterion is helpful, i.e. a greater
value is desirable. Equation (2) can be used to normalize nonbeneficial criteria.
h
i
ðyij Þ min yij ; i ¼ 1; 2; . . . ; m
(1)
xi;j ¼ max yij ; i ¼ 1; 2; . . . ; m min yij ; i ¼ 1; 2; . . . ; m
h
i
max yij ; i ¼ 1; 2; . . . ; m ðyij Þ
xi;j ¼ max yij ; i ¼ 1; 2; . . . ; m min yij ; i ¼ 1; 2; . . . ; m
(2)
3.2.2 Step 2: Define the reference sequence. The performance numbers will be between 0
and 1 after the grey relation generating operation. If the value xij, which is normalized using
the grey relation generating technique, is equal to or nearer to 1 than the value of the other
alternative for a criterion j, it signifies that alternative I’s performance is the best for that
criterion j. As a result, if all of an alternative’s performance numbers are close to or equal to
1, it will be the best decision. The reference alternative is defined as X0 = (x01, x02,. . .,x0j,. . .,
x0n) = (1,1,. . .,1,. . .,. . .,1) and seeks to discover the alternative with the most similar
comparability sequence to the reference sequence.
3.2.3 Step 3: Calculate the grey relational coefficient (W). To establish how close xij is to
x0j, the grey relational coefficient is used. Equation (3) can be used to compute the grey
relationship coefficient. The greater the value of W, the closer xij and x0i are to each other.
Wðx0;i ; xi;j Þ ¼
Dmin þ z Dmax
ð for i ¼ 1; 2; . . . ; m and j ¼ 1; 2; . . . nÞ
Di;j þ z Dmax
(3)
where W (x0,i, xi,j) is the grey relational coefficient between xi,j and x0,i, Di,j = jx0,j xijj
Dmin= min {Di,j,1,2,. . .,m; j = 1,2,. . .,n}
Dmaxn= max {Di,j,1,2,. . .,m; j = 1,2,. . .,n}and z is the distinguish coefficient ( z [ [0,1]),
generally taken as 0.5.
The purpose of the distinguishing coefficient is to expand or compress the range of the
grey relational coefficient.
3.2.4 Step 4: Compute the grey relational grade. After calculating the grey relational
coefficient W (x0i, xij), the grey relational grade can be calculated using the following
equation:
Cðx0 ; xi Þ ¼
n
X
wj Wðxi ; xij Þ ð for i ¼ 1; 2; . . . ; mÞ
(4)
j¼1
where
n
X
wj ¼ 1
j¼1
and the weight of the jth criteria, wj, is determined by the decision-maker. The level of
correlation between the reference sequence and the comparability sequence is shown by the
grey relational grade. If an alternative’s comparability sequence has the greatest grey
relational grade with the reference sequence, it signifies the comparability sequence is the
most similar to the reference sequence, and that option is the best choice.
4. Data analysis and results
For the research questions given in this research paper, there are 11 decision-makers (DMs)
who belong to top management and help ABC Pvt. Ltd. with their best practices. These 10
DMs (DM1 to DM11) each have a good experience. From the source of literature and
semistructural interviews with these identified decision-makers, we prepared a list of 20 key
supply chain challenges and 20 opportunities implemented by this pharmaceutical company
to manage the supply chain process during the COVID-19 pandemic. Further, the key supply
chain strategies have been analyzed by using an MCDM technique GRA to find out their
priority significance in the context of the pharmaceutical company. Based on DMs’ (DM1 to
DM11) experience, scores have been composed for all these key supply chain challenges.
Table 3 represents the scores of the decision matrix for the individual key supply chain
challenges.
The main process of GRA methodology begins by using Step 1, i.e. translating the score
of all the key supply chain challenges into a comparability normalized sequence. The
normalized values of this decision matrix are given in Table 4.
Based on this normalized sequence, and by using Step 2, reference sequences are
determined and presented in Table 5. Using Step 3, the grey relational coefficients between
all the comparability sequences and the reference sequence are computed and presented in
Table 6. Now using Step 4, the grey relational grade between the reference sequence and
every comparability sequence is calculated and presented in Table 7. The highest the grade
the best will be the choice, so accordingly, based on this calculated grey relational grade, the
ranking of these key supply chain challenges that identified and managed the supply chain
Supply chain
distribution
during
COVID-19
S. N. Key supply chain challenges DM1 DM2 DM3 DM4 DM5 DM6 DM7 DM8 DM9 DM10 DM11
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Min
Max
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
5
4
3
4
4
2
4
5
4
4
4
5
4
3
4
5
3
4
4
4
2
5
4
4
3
3
3
3
4
4
2
2
2
4
4
3
3
4
5
4
4
4
2
5
4
5
5
4
4
3
4
5
3
4
2
4
3
4
5
4
4
5
2
4
2
5
4
5
4
5
5
3
4
5
4
4
2
5
3
4
5
5
5
5
2
4
2
5
2
5
5
5
5
5
4
5
4
4
2
5
2
2
5
5
2
5
2
5
2
5
4
5
5
5
3
5
4
3
2
2
4
3
4
4
2
5
4
4
4
4
2
5
3
4
5
5
5
4
3
5
4
4
3
5
3
3
4
4
2
4
2
4
2
5
3
5
5
5
5
4
5
5
3
3
3
5
3
5
5
3
3
5
4
5
3
5
3
5
5
5
5
4
5
5
3
3
3
5
3
4
5
3
3
5
3
5
3
5
4
5
5
4
5
5
5
5
2
2
3
5
4
4
4
5
4
4
4
4
2
5
3
4
4
4
4
3
4
4
4
4
4
4
4
4
4
4
4
5
5
4
3
5
Table 3.
The scores of the
decision matrix (for
challenges)
Challenges
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Min
Max
Table 4.
Normalized values of
decision matrix (for
challenges)
S N.
1
0.66667
0.33333
0.66667
0.66667
0
0.66667
1
0.66667
0.66667
0.66667
1
0.66667
0.33333
0.66667
1
0.33333
0.66667
0.66667
0.66667
0
1
DM1
0.66667
0.66667
0.33333
0.33333
0.33333
0.33333
0.66667
0.66667
0
0
0
0.66667
0.66667
0.33333
0.33333
0.66667
1
0.66667
0.66667
0.66667
0
1
DM2
0.66667
1
1
0.66667
0.66667
0.33333
0.66667
1
0.33333
0.66667
0
0.66667
0.33333
0.66667
1
0.66667
0.66667
1
0
0.66667
0
1
DM3
0.66667
1
0.66667
1
1
0.33333
0.66667
1
0.66667
0.66667
0
1
0.33333
0.66667
1
1
1
1
0
0.66667
0
1
DM4
0
1
1
1
1
1
0.66667
1
0.66667
0.66667
0
1
0
0
1
1
0
1
0
1
0
1
DM5
0.66667
1
1
1
0.33333
1
0.66667
0.33333
0
0
0.66667
0.33333
0.66667
0.66667
0
1
0.66667
0.66667
0.66667
0.66667
0
1
DM6
0.33333
0.66667
1
1
1
0.66667
0.33333
1
0.66667
0.66667
0.33333
1
0.33333
0.33333
0.66667
0.66667
0
0.66667
0
0.66667
0
1
DM7
0
1
1
1
1
0.5
1
1
0
0
0
1
0
1
1
0
0
1
0.5
1
0
1
DM8
0
1
1
1
1
0.5
1
1
0
0
0
1
0
0.5
1
0
0
1
0
1
0
1
DM9
0.66667
1
1
0.66667
1
1
1
1
0
0
0.33333
1
0.66667
0.66667
0.66667
1
0.66667
0.66667
0.66667
0.66667
0
1
DM10
0
0.5
0.5
0.5
0.5
0
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
1
1
0.5
0
1
DM11
JGOSS
Cha.
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
S. N.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Min
Max
DM2
0.333333
0.333333
0.666667
0.666667
0.666667
0.666667
0.333333
0.333333
1
1
1
0.333333
0.333333
0.666667
0.666667
0.333333
0
0.333333
0.333333
0.333333
0
1
DM1
0
0.333333
0.666667
0.333333
0.333333
1
0.333333
0
0.333333
0.333333
0.333333
0
0.333333
0.666667
0.333333
0
0.666667
0.333333
0.333333
0.333333
0
1
0.333333
0
0
0.333333
0.333333
0.666667
0.333333
0
0.666667
0.333333
1
0.333333
0.666667
0.333333
0
0.333333
0.333333
0
1
0.333333
0
1
DM3
0.333333
0
0.333333
0
0
0.666667
0.333333
0
0.333333
0.333333
1
0
0.666667
0.333333
0
0
0
0
1
0.333333
0
1
DM4
1
0
0
0
0
0
0.333333
0
0.333333
0.333333
1
0
1
1
0
0
1
0
1
0
0
1
DM5
0.333333
0
0
0
0.666667
0
0.333333
0.666667
1
1
0.333333
0.666667
0.333333
0.333333
1
0
0.333333
0.333333
0.333333
0.333333
0
1
DM6
0.666667
0.333333
0
0
0
0.333333
0.666667
0
0.333333
0.333333
0.666667
0
0.666667
0.666667
0.333333
0.333333
1
0.333333
1
0.333333
0
1
DM7
1
0
0
0
0
0.5
0
0
1
1
1
0
1
0
0
1
1
0
0.5
0
0
1
DM8
1
0
0
0
0
0.5
0
0
1
1
1
0
1
0.5
0
1
1
0
1
0
0
1
DM9
0.333333
0
0
0.333333
0
0
0
0
1
1
0.666667
0
0.333333
0.333333
0.333333
0
0.333333
0.333333
0.333333
0.333333
0
1
DM10
0
0.333333
0.666667
0.333333
0.333333
1
0.333333
0
0.333333
0.333333
0.333333
0
0.333333
0.666667
0.333333
0
0.666667
0.333333
0.333333
0.333333
0
1
DM11
Supply chain
distribution
during
COVID-19
Table 5.
Deviation sequence
values of decision
matrix (for
challenges)
Cha.
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 6.
Grey relation
coefficient of decision
matrix (for
challenges)
S. N.
1
0.6
0.428571
0.6
0.6
0.333333
0.6
1
0.6
0.6
0.6
1
0.6
0.428571
0.6
1
0.428571
0.6
0.6
0.6
DM1
0.6
0.6
0.428571
0.428571
0.428571
0.428571
0.6
0.6
0.333333
0.333333
0.333333
0.6
0.6
0.428571
0.428571
0.6
1
0.6
0.6
0.6
DM2
0.6
1
1
0.6
0.6
0.428571
0.6
1
0.428571
0.6
0.333333
0.6
0.428571
0.6
1
0.6
0.6
1
0.333333
0.6
DM3
0.6
1
0.6
1
1
0.428571
0.6
1
0.6
0.6
0.333333
1
0.428571
0.6
1
1
1
1
0.333333
0.6
DM4
0.333333
1
1
1
1
1
0.6
1
0.6
0.6
0.333333
1
0.333333
0.333333
1
1
0.333333
1
0.333333
1
DM5
0.6
1
1
1
0.428571
1
0.6
0.428571
0.333333
0.333333
0.6
0.428571
0.6
0.6
0.333333
1
0.6
0.6
0.6
0.6
DM6
0.428571
0.6
1
1
1
0.6
0.428571
1
0.6
0.6
0.428571
1
0.428571
0.428571
0.6
0.6
0.333333
0.6
0.333333
0.6
DM7
0.333333
1
1
1
1
0.5
1
1
0.333333
0.333333
0.333333
1
0.333333
1
1
0.333333
0.333333
1
0.5
1
DM8
0.333333
1
1
1
1
0.5
1
1
0.333333
0.333333
0.333333
1
0.333333
0.5
1
0.333333
0.333333
1
0.333333
1
DM9
0.6
1
1
0.6
1
1
1
1
0.333333
0.333333
0.428571
1
0.6
0.6
0.6
1
0.6
0.6
0.6
0.6
DM10
0.333333
0.5
0.5
0.5
0.5
0.333333
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
1
1
0.5
DM11
JGOSS
S.N.
Challenges
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
GRG
Rank
0.523810
0.845455
0.814286
0.793506
0.777922
0.595671
0.684416
0.866234
0.454113
0.469697
0.414286
0.829870
0.471429
0.547186
0.732900
0.724242
0.551082
0.818182
0.506061
0.700000
15
2
5
6
7
12
11
1
19
18
20
3
17
14
8
9
13
4
16
10
Note: GRG = Grey Relation Grades
Supply chain
distribution
during
COVID-19
Table 7.
The summary of
grey relation grades
and ranking (for
challenges)
process during the impact of the COVID-19 is shown in Figure 2. The final rank of key
supply chain challenges is C8 > C2 > C12 > C18 > C3 > C4 > C5 > C15 > C16 > C20 >
C7 > C6 > C17 > C14 > C1 > C19 > C13 > C10 > C9 > C11. Table 7 shows “Impact of
political factor” (C8), “Delay in import process” (C2), “Weak internet connection” (C12) while
“Weak knowledge of the use of digital platform” (C10), “Poor information sharing in online
by employees” (C9), “Information flow from top management to operational level” (C11)
have been identified as top and bottom three key challenges, respectively. Afterward, the
positions of other challenges are measured in-between two ends. Moreover, it helps to
improve the supply chain distribution level and good planning to overcome the COVID-19
pandemic with appropriate decision-making.
Table 8 represents the scores of the decision matrix for the individual key supply chain
opportunities. In the similar way, we have followed various GRA steps (Steps 1, 2, 3 and 4)
as above have been followed and analyzed to measure the rank of these managing the
Histogram
1
0.8
0.6
0.4
0.2
0
GRG
C1
C2
C3
C4
C5
C6
C7
C8
C9
C10
C11
C12
C13
C14
C15
C16
C17
C18
C19
C20
Figure 2.
Ranking of the key
supply chain
challenges
JGOSS
Table 8.
The scores of the
decision matrix (for
managing the
opportunities)
S. N.
Opportunities
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Min
Max
MO1
MO2
MO3
MO4
MO5
MO6
MO7
MO8
MO9
MO10
MO11
MO12
MO13
MO14
MO15
MO16
MO17
MO18
MO19
MO20
DM1
DM2
DM3
DM4
DM5
DM6
DM7
DM8
DM9
DM10
DM11
2
4
4
4
4
4
4
3
4
4
4
4
5
5
4
3
3
4
5
4
2
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
4
4
3
4
4
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
4
4
3
3
4
4
3
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
4
4
3
4
4
4
4
4
5
5
2
4
4
4
5
5
4
4
5
4
3
3
4
5
2
5
5
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
5
4
4
4
5
4
4
4
3
5
4
4
4
4
4
5
4
5
4
4
5
3
3
4
4
3
5
5
3
3
5
5
5
5
5
5
3
4
3
5
3
3
5
2
2
4
3
2
5
5
3
3
5
5
5
5
5
5
4
3
4
3
5
3
5
2
2
4
3
2
5
4
3
3
2
3
3
3
4
3
4
4
4
5
5
3
5
4
4
3
4
2
5
5
5
4
5
5
5
4
4
3
4
4
4
3
4
3
3
4
4
4
5
3
5
opportunities, presented in Tables 9, 10, 11 and 12, respectively. The highest the grade the
best will be the choice, so accordingly, on the basis of this calculated grey relational grade,
the ranking of these opportunities that need to manage the supply chain process during the
impact of the COVID-19 is shown in Figure 3. The final rank of key supply chain challenges
is MO5 > MO1 > MO6 > MO14 > MO16 > MO13 > MO4 > MO11> MO8 > MO20 >
MO9 > MO7 > MO12 > MO19 > MO2 > MO10 > MO3 > MO15 > MO17 > MO18.
Table 12 shows the “Inventory management” (MO5), “Selection of transport method” (MO1),
“Operational cost” (MO6) and “Marketing and brand Innovation” (MO15), “Online delivery
of products” (MO17), “E-commerce enablement (launching applications, tracking system)”
(MO18) are identified as the top and bottom three managing the opportunities, respectively.
Afterward, the final rank of other opportunities is measured in between two ends.
5. Discussion and findings
This work explicitly indicates the challenges and how to manage the opportunities to
mitigate the challenges through uncertainties, real-time information and agility in the digital
supply chain of Pharmaceutical distribution companies in Myanmar. Research results
reveal that COVID-19 and political conflict immensely surge and impact the pharmaceutical
enterprise in Myanmar. There are 20 challenges and 20 factors of managing opportunities.
The factors used in the study are extracted from the existing literature by the fact that
current affairs, geographical conditions, industrial infrastructure and secondary data of the
company profile emphasize a particular business context in a particular country.
Participants are asked to answer these factors with five-point Likert scales. Next, the GRA
method is applied to analyze the data, and the results rank the most and the least critical
factors for both challenges and countermeasures of the opportunities.
DM1
0
0.66667
0.66667
0.66667
0.66667
0.66667
0.66667
0.33333
0.66667
0.66667
0.66667
0.66667
1
1
0.66667
0.33333
0.33333
0.66667
1
0.66667
0
1
Opp.
MO1
MO2
MO3
MO4
MO5
MO6
MO7
MO8
MO9
MO10
MO11
MO12
MO13
MO14
MO15
MO16
MO17
MO18
MO19
MO20
S. N.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Min
Max
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
0
1
1
0
1
DM2
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
1
0.5
0.5
0
0
0.5
0.5
0
1
DM3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
0
1
DM4
0.66667
0.66667
0.66667
0.66667
1
1
0
0.66667
0.66667
0.66667
1
1
0.66667
0.66667
1
0.66667
0.33333
0.33333
0.66667
1
0
1
DM5
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
DM6
0.5
0.5
0.5
0
1
0.5
0.5
0.5
0.5
0.5
1
0.5
1
0.5
0.5
1
0
0
0.5
0.5
0
1
DM7
1
0.33333
0.33333
1
1
1
1
1
1
0.33333
0.66667
0.33333
1
0.33333
0.33333
1
0
0
0.66667
0.33333
0
1
DM8
1
0.33333
0.33333
1
1
1
1
1
1
0.66667
0.33333
0.66667
0.33333
1
0.33333
1
0
0
0.66667
0.33333
0
1
DM9
0.66667
0.33333
0.33333
0
0.33333
0.33333
0.33333
0.66667
0.33333
0.66667
0.66667
0.66667
1
1
0.33333
1
0.66667
0.66667
0.33333
0.66667
0
1
DM10
1
1
0.5
1
1
1
0.5
0.5
0
0.5
0.5
0.5
0
0.5
0
0
0.5
0.5
0.5
1
0
1
DM11
Supply chain
distribution
during
COVID-19
Table 9.
Normalized values of
decision matrix (for
managing the
opportunities)
JGOSS
This thesis has identified 20 critical factors of challenges during a pandemic. The impact of
political factors (C8) is indicated as the most crucial aspect being faced in the digital supply
chain of Myanmar’s pharmaceutical company. Political instability increases uncertainties
related to all areas of supply chain activities such as inventory management, transportation,
high cost and operations. Fear of security collapse forces the people to purchase the
excessive number of products that causes the higher demand. A sudden high level of
demand brings the shortage of raw materials together. To meet the higher demand, the
manufacturing company attempts a higher production rate. However, both pandemic
restrictions, e.g. lockdown and several constraints caused by political issues interrupt the
transportation and delay in import process (C2) which is standing at the second-ranked
place in this study. Delay in import process is a severe problem for the case pharmaceutical
distribution company because its product merchandising is mostly from ASIAN countries
such as Singapore, Malaysia and Thailand which also suffer an operational interruption of
COVID-19 outbreak. In addition, another strictly constrained factor is a weak internet
connection (C12) because the internet is the key in the digital supply chain during the
pandemic. On the other hand, weak knowledge of the use of the digital platform (C10) is
ranked as the third least crucial factor followed by poor information sharing online by
employees (C9) as the second least important factor and information flow from top
management to operational level (C11) as the least vital factor. Therefore, this study affirms
some factors belonging to real-time information do not impact significantly on digital
supply chain during the pandemic.
During the pandemic, managing the opportunities is the key performance to mitigating
the risks and challenges within and across the digital supply chain. After investigating 20
factors, inventory management (MO5) is listed as the most critical factor. Panic buying
caused by pandemic and political instability directly and significantly impacts inventory
control. Logistics restrictions due to COVID-19 spread also have negative effects on
inventory management. To overcome it, selection of the transport method (MO1) plays the
second most pivotal aspect to operate at low cost with good quality. Since pricing becomes a
matter, reducing the waste of operational cost (MO6) resides at the core of operation
management as the third most important element. Surprisingly, marketing and brand
innovation (MO15), which is always a paramount thing in normal circumstances, is the third
least important component during pandemic followed by online delivery of the product
(MO17) and E-commerce enablement (MO19), second least and first least items. It shows that
e-commerce adaption and online delivery are not significantly important in managing
opportunities for the pharmaceutical company of Myanmar, wherein internet access is one
of the most challenging aspects.
Histogram
1
0.8
0.6
0.4
0.2
Figure 3.
Ranking of managing
the supply chain
opportunities
0
GRG
O1
O2
O3
O4
O5
O6
O7
O8
O9
O10
O11
O12
O13
O14
O15
O16
O17
O18
O19
O20
DM1
1
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.666667
0.333333
0.333333
0.333333
0.333333
0
0
0.333333
0.666667
0.666667
0.333333
0
0.333333
0
1
Opp.
MO1
MO2
MO3
MO4
MO5
MO6
MO7
MO8
MO9
MO10
MO11
MO12
MO13
MO14
MO15
MO16
MO17
MO18
MO19
MO20
S. N.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Min
Max
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
0
1
DM2
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0
0.5
0.5
1
1
0.5
0.5
0
1
DM3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
1
DM4
0.333333
0.333333
0.333333
0.333333
0
0
1
0.333333
0.333333
0.333333
0
0
0.333333
0.333333
0
0.333333
0.666667
0.666667
0.333333
0
0
1
DM5
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
1
1
0
1
DM6
0.5
0.5
0.5
1
0
0.5
0.5
0.5
0.5
0.5
0
0.5
0
0.5
0.5
0
1
1
0.5
0.5
0
1
DM7
0
0.666667
0.666667
0
0
0
0
0
0
0.666667
0.333333
0.666667
0
0.666667
0.666667
0
1
1
0.333333
0.666667
0
1
DM8
0
0.666667
0.666667
0
0
0
0
0
0
0.333333
0.666667
0.333333
0.666667
0
0.666667
0
1
1
0.333333
0.666667
0
1
DM9
0.333333
0.666667
0.666667
1
0.666667
0.666667
0.666667
0.333333
0.666667
0.333333
0.333333
0.333333
0
0
0.666667
0
0.333333
0.333333
0.666667
0.333333
0
1
DM10
0
0
0.5
0
0
0
0.5
0.5
1
0.5
0.5
0.5
1
0.5
1
1
0.5
0.5
0.5
0
0
1
DM11
Supply chain
distribution
during
COVID-19
Table 10.
Deviation sequence
values of decision
matrix (for managing
the opportunities)
Opp.
MO1
MO2
MO3
MO4
MO5
MO6
MO7
MO8
MO9
MO10
MO11
MO12
MO13
MO14
MO15
MO16
MO17
MO18
MO19
MO20
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Table 11.
Grey relation
coefficient of decision
matrix (for managing
the opportunities)
S. N.
0.333333
0.6
0.6
0.6
0.6
0.6
0.6
0.428571
0.6
0.6
0.6
0.6
1
1
0.6
0.428571
0.428571
0.6
1
0.6
DM1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.333333
1
1
0.333333
1
1
DM2
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
1
0.5
0.5
0.333333
0.333333
0.5
0.5
DM3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.333333
1
1
DM4
0.6
0.6
0.6
0.6
1
1
0.333333
0.6
0.6
0.6
1
1
0.6
0.6
1
0.6
0.428571
0.428571
0.6
1
DM5
1
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
0.333333
1
0.333333
0.333333
DM6
0.5
0.5
0.5
0.333333
1
0.5
0.5
0.5
0.5
0.5
1
0.5
1
0.5
0.5
1
0.333333
0.333333
0.5
0.5
DM7
1
0.428571
0.428571
1
1
1
1
1
1
0.428571
0.6
0.428571
1
0.428571
0.428571
1
0.333333
0.333333
0.6
0.428571
DM8
1
0.428571
0.428571
1
1
1
1
1
1
0.6
0.428571
0.6
0.428571
1
0.428571
1
0.333333
0.333333
0.6
0.428571
DM9
0.6
0.428571
0.428571
0.333333
0.428571
0.428571
0.428571
0.6
0.428571
0.6
0.6
0.6
1
1
0.428571
1
0.6
0.6
0.428571
0.6
DM10
1
1
0.5
1
1
1
0.5
0.5
0.333333
0.5
0.5
0.5
0.333333
0.5
0.333333
0.333333
0.5
0.5
0.5
1
DM11
JGOSS
S.N.
Opp.
GRG
Rank
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
MO1
MO2
MO3
MO4
MO5
MO6
MO7
MO8
MO9
MO10
MO11
MO12
MO13
MO14
MO15
MO16
MO17
MO18
MO19
MO20
0.775758
0.619913
0.574459
0.700000
0.805628
0.760173
0.654113
0.678355
0.663203
0.605628
0.687446
0.641991
0.745022
0.760173
0.535065
0.745022
0.511255
0.466234
0.641991
0.671861
2
15
17
7
1
3
12
9
11
16
8
13
6
4
18
5
19
20
14
10
Notes: For managing the opportunities; GRG = Grey Relation Grades
5.1 Theoretical implications
The study finds the highest importance level of inventory management, selection of the
supplier and transport method and reducing the waste of operational cost for managing the
opportunities in the digital supply chain while the most challenging concerns emerge as
the impact of political factor, delay in the import process and weak internet connection.
Existing literature points out that inventory should be managed effectively to handle the
surging demand during pandemics (Butt, 2021). Since the supply chain has several
stakeholders along the chain, delay in the process is a common bottleneck, and it should be
controlled by all stakeholders (Abdallah and Nabass, 2018). One of the factors affecting
process hesitation is transportation system choice which is of great importance to
consumers during the COVID-19 crisis (Ramanathan et al., 2021). The choice of transport
also impacts on cost reduction, for example, the cost for regular merchandising, cost for
urgent purchases and cost of expired products (Franco and Alfonso-Lizarazo, 2020).
Surprisingly, while e-commence is growing around the world (Yang and Lin, 2021), its
significance cannot be seen in this study. At last, a factor of political instability is the key
contribution of this study by placing it as the highest challenging level.
5.2 Managerial implications
This study has several implications from the managerial perspective. The most challenging
factor, political conflict, is mostly associated with developing countries like Myanmar which
has serious political problems. Business leaders and managers in Myanmar should be aware
of the fact that it can immensely impact on digital supply chain system during a pandemic.
Another factor is a weak internet connection. We all have perceived that today’s market is a
very competitive market with the effective use of e-commence, but it does not seem working
in Myanmar due to the weak internet connection or it seems to hamper to adopt it. As the
Supply chain
distribution
during
COVID-19
Table 12.
The summary of
grey relation grades
and ranking
JGOSS
supply chain has many stakeholders, business managers should take care of possible
interruptions to fulfill customer satisfaction. Moreover, the choice of transportation method
has been received adequate attention, and it remains the most important aspect to manage
the opportunities during the pandemic. Business leaders and future researchers should also
be aware of the other factors, such as demand postponement, suppliers’ performance
concerns, surging demand, product pricing and geographical restriction on logistical flow,
which are ranked in the middle range of importance level by the MCDM method of this
study.
6. Conclusions, limitations and future scope
The study aims to identify the key supply chain challenges and develop the opportunity to
manage the process during the COVID-19 pandemic. During this unforeseen situation, the
company needs to purchase and procure raw materials from various suppliers, store them in
warehouses, continue to produce the products and distribute the products. As a leading
pharmaceutical company, not everything is easy to manage for it appropriately, so the
company identifies its different challenges and tries to mitigate and manage them. Further,
the GRA methodology has been used to prioritize them as different key supply chain
challenges and opportunities. From the previous literature and semistructural interview
with the top management of this pharmaceutical company, a total of 20 challenges and 20
opportunities are identified, highlighted and measured. Based on the GRA method and grey
relational grade calculation, we found the ranking of these challenges and opportunities that
need to manage first in the supply chain process during the impact of the COVID-19. The
company needs to concentrate and tackle these challenges to smooth the functioning of the
supply chain process and set the opportunity to achieve the business goals. These
challenges and the opportunities are managed through three categories such as
uncertainties, real-time information and agility in the digital supply chain of a
pharmaceutical distribution company in Myanmar.
The present study has its limitations in that the decision and opinion were obtained from
only the top management level of the organization. It is a very tough time during the
COVID-19 outbreak for the company to maintain the performance level of the supply chain
according to the end user demand. Another limitation is, the current study was undertaken
solely from the perspective of the pharmaceutical company, but similar research might be
conducted in other types of businesses and other developing nations in the future studies.
The directions for future research are explained here in the following points. There is an
excellent scope to establish a structural relationship model between these key supply chain
challenges and opportunities, and another scope is to check the statistical validation of the
relationship model and preference ranking methods considering different various methods
like analytical hierarchy process (AHP), analytical network process (ANP), technique for
order of preference by similarity to ideal solution (TOPSIS), interpretive structural method
(ISM), etc. In the future study, this study can be considered for multisector organizations and
focused on a comparative study with various MCDM methods. In the future study, the
factors such as uncertainty, real-time information and agility factors can be assumed as
factors; we can categorize them into main categories and then their subcategories factors
and prioritize them through individual and group decision-maker’s contexts considering
AHP and ANP approach. Many more related factors can be identified from the previous
studies and ground reality to enhance the supply chain distribution performance. The
hybrid MCDM techniques like TOPSIS and VIekriterijumsko KOmpromisno Rangiranje can
be used to validate the model and improve the power of relative performance measures in
the future. Similar research work might be conducted for other developing countries to
improve the supply chain process during the COVID-19 outbreak. Comparative analysis can
be done for supply chain performance. Structural equation modeling can also be considered
to develop the constructive relationship between identified factors on a continuous scale to
check the impact of performance. Some other modeling techniques, such as the Bayesian
belief networks, could use in the production and distribution process that could significantly
increase the quality of production with various operations, productivity and performance in
the future scope of this study. The readers of the study or scholars/researchers can enhance
it, as there is still a vast scope even after this research, which can be fulfilled.
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Appendix. Questionnaire
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About the authors
Vimal Kumar is an Assistant Professor at the Chaoyang University of Technology, Taichung,
Taiwan (R.O.C.) in the Department of Information Management. He completed his Postdoctoral
Research at the Chaoyang University of Technology, Taichung, Taiwan (R.O.C.) in the Department of
Business Administration in the domain of Technological Innovation and Patent Analysis. He has
served as an Assistant Professor under TEQIP III, an initiative of MHRD, Govt. of India at AEC
Guwahati in the Department of Industrial and Production Engineering. Prior to joining AEC, he
served as an Assistant Professor at MANIT, Bhopal, in the Department of Management Studies and
also served as Visiting Faculty at IMT Nagpur. He obtained his PhD in the domain of TQM and
Manufacturing Strategy in the year 2017 and Masters in Supply Chain Management from the
Department of Industrial and Management Engineering, IIT Kanpur, in the year 2012. He graduated
(BTech) in Manufacturing Technology from JSS Academy of Technical Education Noida in the year
2010. He has published 41 articles in reputable international journals and presented 24 papers at
international conferences. His research paper entitled “Time Table Scheduling for Educational Sector
on an E-Governance Platform: A Solution from an Analytics Company” has been selected for best
paper award at the International Conference on Industrial Engineering and Operations Management
(IEOM) held in Bandung, Indonesia, March 6–8, 2018. He was also invited to serve as session chair of
session on “Energy Related Awareness” held on September 19, 2018, at iCAST 2018, IEEE
International Conference on Awareness Science and Technology and “Lean Six Sigma” at the
International Conference on Industrial Engineering and Operations Management (IEOM-2018) at
Bandung, Indonesia and “Quality Control and Management” at the International Conference on
Industrial Engineering and Operations Management (IEOM-2016) at Kuala Lumpur, Malaysia. He
has been appointed as an editorial board member in the IEEE-TEMS Journal from January 1, 2022 to
December 31, 2024. He is a contributing author in international journals including Journal of
Informetrics, Technology in Society, CLSCN, Supply Chain Management: An International Journal,
IJOA, JEEE, BSE, TFSC, JKM, CSREM, IJPPM, IJQRM, IJPMB, IJPQM, IJBIS, AJOR, The TQM
Journal and Benchmarking: An International Journal, etc., and also a guest reviewer of a reputable
journal like IEEE-TEMS, JOI, IJPPM, IJQRM, TQM and Business Excellence, The TQM Journal,
Benchmarking: An International Journal, Journal of Asia Business Studies and JSIT.
Kyaw Zay Ya is a current PhD research scholar focusing on logistics and supply chain,
Department of Business Administration, Chaoyang University of Technology, Taiwan. He has got
his master’s degree in Vocational Education (Mechanical) from Universitas Negeri Padang, Indonesia,
and he gained his Bachelor of Engineering (Mechanical) degree in Thanlyin Technological
University, Myanmar. He has published four research papers and one conference paper in
international journals and conferences. Kyaw Zay Ya is the corresponding author and can be
contacted at: kzayya111@gmail.com
Kuei-Kuei Lai is the Vice President and a Professor of the Department of Business Administration,
Chaoyang University of Technology Taichung, Taiwan. He has served as a Professor and the
Chairman of the Department of Business Administration, National Yunlin University of Science and
Technology, Taiwan. He received his PhD degree in the Graduate Institute of Management Sciences
from Tamkang University in Taiwan. His research interest focuses on management of technology in
patent citation analysis, patent portfolio and patent family and technological forecasting.
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