Reshaping healthcare supply chain using chain-of-things technology and key lessons experienced from COVID-19 pandemic

Abstract

The COVID-19 (Corona virus disease 2019) pandemic continues to slash through the entire humanity on the earth causing an international health crisis and financial uncertainty. The pandemic has formed a colossal disruption in supply chain networks. It has caused piling higher mortality in patients with comorbidities and generated a surging demand for critical care equipment, vaccines, pharmaceuticals, and cutting-edge technologies. Personal protective equipment, masks, ventilators, testing kits, and even commodities required for daily care have been scarce as lockdown and social distancing guidelines have kicked in. Amidst COVID-19, implementing and executing key processes of the healthcare supply chain (HSC) in a secured, trusted, effective, universally manageable, and the traceable way is perplexing owing to the fragile nature of the HSC, which is susceptible to redundant efforts and systemic risks that can lead to adverse impacts on consumer health and safety. Though the crisis shone a harsh light on the cracks and weaknesses of the HSC, it brings some significant insights into how HSC can be made more resilient and how healthcare industries figure out solutions to mitigate disruptions. While there are innumerable experiences learned from the disruption of this crisis, in this paper, five important areas to analyze the most vital and immediate HSC enhancements including building a resilient supply chain, thinking localization, implementing reliable reverse logistics, breaking down extant silos to achieve end-to-end visibility, and redesigning HSC using digitalization are emphasized. This work identifies important features related to CoT and HSC. Also, this study links these lessons to a potential solution through Chain of Things (CoT) technology. CoT technology provides a better way to monitor HSC products by integrating the Internet of Things (IoT) with blockchain networks. However, such an integrated solution should not only focus on the required features and aspects but also on the correlation among different features. The major objective of this study is to reveal the influence path of CoT on smart HSC development. Hence, this study exploits (i) fuzzy set theory to eliminate redundant and unrelated features; (ii) the Decision-Making and Experimental Evaluation Laboratory (DEMATEL) method to handle the intricate correlation among different features. This fuzzy-DEMATEL (F-DEMATEL) model attempts to direct CoT technology towards smart HSC by identifying the most influencing factors and investors are recommended to contribute to the development of application systems. This work also demonstrates how CoT can act a vital role in handling the HSC issues triggered by the pandemic now and in the post-COVID-19 world. Also, this work proposes different CoT design patterns for increasing opportunities in the HSC network and applied them as imperative solutions for major challenges related to traditional HSC networks.

1. Introduction

The highly infectious corona virus and the associated diseases were originally identified in Wuhan City of China in early December 2019 [[1], [2]]. As of now, it has spread like wildfire and marking its existence in almost every country (220 in total) and independent territories across the globe [3]. On 11 March 2020, the World Health Organization (WHO) announced COVID-19 as a pandemic. The pandemic is hastily pushing the healthcare sector just before its snapping point; already, hospitals are stunned with patients who tested positive and suspected cases expecting diagnostic confirmation. Based on the WHO report, the total confirmed COVID-19 positive cases have reached 183,934,913 and the death toll stands at 3,985,022 as of 5^th July 2021 [4]. The pandemic has made a substantial impact on the existing treatment methods and healthcare facilities. There are still many qualms including the virus’ origins, development, and detail as well as unsought fears associated with the COVID-19.

To alleviate the risk of infection, all most all the countries enforced drastic lockdowns and employed community quarantines or isolation procedures on the entire inhabitants. Individuals are instructed to circumvent social gatherings and international or even domestic nomads to stop the further spread of the virus. This has made people stay in their homes unless they have to avail themselves of essential services or look for any therapeutic action. In consort with this, large organizations such as Apple, Twitter, Microsoft, Salesforce, Google, etc. have implemented compulsory work-from-home strategies. The production plants are temporarily shuttered or running with reduced manpower [5]. Organizations have had to struggle with unpredictable fluctuations in customer demand, production interruption, and supply chain disruptions [6]. These restrictions are causing a business stoppage in several industries, and a vast majority have struggled with important challenges in nearly every aspect of their processes.

The financial implications of the pandemic on international trade and global supply chains are important. The entire supply chain — from raw material suppliers to consumers’ delivery docks — is broken up indefinitely. The pandemic cuts global shipment of raw materials and critical parts by approximately $228 billion owing to interruptions of the supply network [7]. According to a survey reported by Capgemini Research Institute, more than 80% of industries being adversely affected by the pandemic and most of them have contended with major challenges as illustrated in Fig. 1 [8]. These include deficiency of critical materials/parts (74%), longer lead times and deferred deliveries (74%), complications in regulating production capacity against sharp spikes and declines in demands (69%), and hitches in planning amongst unpredictable demand (68%). All the enterprises – discrete manufacturing, retail, life sciences, and consumer products – faced similar challenges across their supply networks.

Fig. 1.

Percentage of organizations that encountered considerable challenges across the supply chain during the pandemic (Source [8].

Since the outbreak of COVID-19 continues to have a shocking effect on society and the global economic landscape, healthcare supply networks have been vivid – even irreversibly – affected. In general, clinical trials and research are time-consuming and complex processes. Protocols for medical equipment and pharmaceuticals are stringent, and it takes years to bring standard products to the market. When the drug or medical equipment is ready to be sold, it enters the HSC to reach the end-user. It is no exaggeration to say that in several cases, healthcare products can make the difference between life and death. Hence, it is indispensable that they are accessible when necessary and managed properly to give maximum efficiency when utilized. The HSC includes producers, suppliers, distributors, wholesalers, retailers, physicians, and end-users. The major goals of the HSC management are: (i) supplying original medicinal goods and services to the providers and patients in a timely manner; (ii) plummeting the effect of ecological conditions during shipping and storage of products; (iii) providing end-to-end visibility and control to the governing bodies and manufacturers; (iv) guaranteeing trust among participants; and (v) protecting the valuable data related to the products and supply chain operations.

In spite of their significance, most of the traditional HSC systems are not achieving the envisioned goals due to their interoperability disputes and security issues during this pandemic situation. Hence, organizations responsible for managing their very complex and fragmented HSC, are calling for dependable technological solutions that offer better outcomes to mitigate the challenges such as product scarcities, shipment deferrals, limited frontline healthcare professionals, support staff, and medical services in hospitals. Moreover, the pandemic forces the entire medical industry, to revisit and transform their HSC modelto tolerate any disruptions in the future. It hastens the adoption of new technologies, proficiencies, and immediate actions to mitigate such potential disruptions and risks along supply chains. Several new technologies are developing to increase visibility across the entire HSC and facilitate a much more resilient and robust supply network.

Advanced information and communications technology (ICT) implements including IoT, cloud computing, artificial intelligence (AI), machine learning, data analytics, robotics, 3D printing, and blockchain technology are bringing innovations to the HSC [[9], [10], [11]]. In the chorus, a volatile business setting is making it all the more requisite. Whether it is a black swan type crisis, an act of terrorism/war, a trade war, supplier bankruptcy, labor dispute, regulatory change, cyberattacks, or a spike or decline in demand for a certain product in a particular area, organizations are learning to count on the unforeseen. Similarly, various drug products, like biopharmaceuticals, vaccines, and cell therapies, need to be conveyed under rigorous ecological conditions where light exposure, humidity, temperature, and other constraints are strongly controlled. The medicinal industry is projected to incur $15 billion annually in product losses due to failures in temperature-controlled logistics. Similarly, the biopharma industry loses around $35 billion per year as a result of temperature variations alone. To rein in these costs, producers, suppliers, and caregivers are more and more relying on tracking techniques that can collect near-real-time data related to the product delivery and present that information on a web platform.

Healthcare product manufacturers have shown keen interest in utilizing IoT to enable their device identification for tracing. HSC managers have employed sensors in both the healthcare products being used and the environment where they are warehoused and transported to monitor the condition of the product in shipping and how it is utilized within the user vicinity. However, building reliable IoT networks in HSC management is challenged by several communication performance dilemmas and security threats [12]. For instance, medical product manufacturers need to secure their supply network and protect their valuable data against data breaches. Hence, a secured business model is mandatory for managing and accessing data from IoT-based medical devices without any security threats to the identity, privacy, and integrity of data managed by those expedients.

Blockchain is a novel technology that can be employed for alleviating potential challenges and risk factors in HSC, mainly when combined with IoT technology [13]. Integrating decentralized logs of blockchain technology with the potential benefits of IoT (i.e., Chain of Things) increases the performance of HSC in monitoring and tracking [14,15]. The concept of CoT technology is a significant contribution toward digital transformation in the supply network. It offers several potential solutions to increase the speed, scalability, and visibility of HSC, evading counterfeit-products trades, and managing product recall, expiration, shortages while enhancing batching, shipping, and inventory management. This study aims to reveal the influence path of CoT on smart HSC development using the DEMATEL method. Hence, the lessons learned from the pandemic as well as the major attributes of CoT have been identified by literature review and by interrogating experts through opinion poll. Then, this study integrate fuzzy set theory and DEMATEL methods to develop F-DEMATEL in order to assess the interconnection between features and reveal the correlation among various hierarchies, disclosing the influence path of CoT on the HSC system. Additionally, this study describes how CoT makes business transactions more transparent, secure, and tamper proof, which can have a huge impact on the performance of the HSC. Furthermore, it will enhance the performance of HSC with live tracking in enhanced end-to-end visibility. Nevertheless, the pandemic has made a colossal disruption in HSC it brings some significant insights into how HSC can be made more robust and how industries figure out solutions to handle disruptions or pandemics. The major contributions of the article are four-fold.

• (1)This study identifies five important aspects including resilience, localization, reverse logistics, end-to-end visibility, and digitalization to build and maintain a most efficient HSC as it returns to a “new normal”.
• (2)This study demonstrates how CoT can act a central role in handling the HSC issues triggered by the pandemic now and future.
• (3)This study proposes a fuzzy-DEMATEL approach to identify the influence path of CoT on the HSC system by deriving the relationship among different features and aspects. Also, this model attempts to direct CoT technology towards smart HSC by identifying the most influencing factors.
• (4)A novel CoT architecture and communication design patterns for increasing opportunities in HSC are proposed and employed them as imperative solutions to mitigate major challenges in traditional HSC networks.
• (5)This study links these lessons to a potential solution through the CoT network. It provides a secure way to monitor medical products by integrating IoT and blockchain technologies.

The remaining sections of the article are framed as follows. The following Section provides key concepts related to CoT technology. In Section III, the key supply chain lessons learned from the COVID-19 pandemic are discussed in detail. Section IV discusses the proposed fuzzy-DEMATEL approach to eliminate redundant features and derive exact relationships among different features. Section V describes the proposed CoT framework to achieve an efficient HSC management system. Section VI links the profound lessons learned from the pandemic to a potential solution through the CoT network. This paper is concluded in Section VII.

2. Revisiting technologies integrated into the chain of things

The convergence of blockchain technology, IoT, AI, cloud computing, and data analytics represents an important fulcrum that provides solid input to the irreversible shift towards Society 5.0 from Industry 4.0 [16]. Moreover, this integration is predicted to considerably impact all the aspects of the business and renovate the way we work within various supply chain networks [17]. The concept of CoT, leveraging the nexus between IoT and blockchain technology, is a significant contribution intended to reform the digital transformation of several platforms [15]. This technology enables organizations to reinforce relationships among their core corporate partners, particularly with current consumers, and to entice new ones. Furthermore, it is used to resolve inherent issues such as identity, security, and interoperability problems related to connected things and to create well-organized pioneering applications in the healthcare supply network. CoT facilitates infrastructure for different communication and transactions environment [18]. It enables several smart things to share transactional data rapidly without mediation or authentication from financial entities and other trusted bodies. It can create immutable logs that can be exchanged and impact the entire product HSC [19,20]. It allows organizations to track and trace their products in a secure way as well as to increase their authority and validity. The net effect would be a significant enhancement in the performance of HSC [21].

2.1. Internet of Things

IoT is a radical technology for all large-scale industries. Currently, it is a key enabler in the digital revolution observed by Industry 4.0 since it can fetch significant innovations and changes across a wide range of application domains [22]. It is a connected crew of things (e.g., sensors, healthcare manoeuvres, etc.), barcodes, quick response (QR) codes, radio-frequency identification (RFID) tags systems, etc. The research predicted that by 2025 there will be 75.44 billion smart things in use and its global market is projected to touch $1.6 trillion [23]. Quick adoption of smart thermostats and medical expedients are adding innumerable connections and opportunities to the consumer world. Consequently, healthcare product manufacturing industries are seeking how they can utilize this trend and transform their interactions with their consumer.

In the earlier days of IoT interactions, disparate edge devices were not performing immense data analysis and manipulation. Nowadays, the devices are communicating with lots of interrelationships and manipulating huge data [24]. Even though the effect of IoT on the industry is still to be fully studied, the advancements of IoT have considerably facilitated the digital transformation of our society which makes its transactions so powerful [25].). The modern IoT technology builds over prevailing digital infrastructures and connects as many things and living objects (people) as possible through appropriate authentication methods. It drives advanced communication patterns and engenders actionable intelligence by integrating analytics of the data exchanged by the associated devices. It enables healthcare organizations to detect, monitor, and track medical products, events, and processes within their corresponding supply networks. In a healthcare supply network, the data collected from the products and IoT devices can be hoarded and assessed to make smart decisions in real-time. When combined with blockchain technology, it provides a wide variety of application scenarios to increase the visibility, business-to-business trust, and performance of medical supply networks.

2.2. Blockchain technology

Blockchain emanated into the limelight as a cryptographically protected and distributed ledger comprising information on transactions and the Bitcoin (i.e., virtual cryptocurrency) in 2008 [26]. Of late, beyond its best-known application of Bitcoin, blockchain has gained prevalent attention and interest from several industries and communities including government [27], healthcare [[28], [29], [30], [31]], finance [32], supply chain [33].), etc. According to a recent forecast by Gartner, the global economy amplified by blockchain will be reached around $176 billion by 2025, then surge to surpass $3.1 trillion by 2030 [34]. Blockchain consists of distributed log for registering times tamped transactions among several nodes in a private or public peer-to-peer (P2P) communication system. It is considered as an increasing list of records, known as “blocks”, which are linked tightly through cryptographic sealing. The cryptographic sealing is used to encrypt places or wallets on the block where work or value is securely stored. These tamper-proof records are managed by a public time-stamping server in a P2P network [35].

Each block in the chain comprises the preceding block hash code, a timestamp, and a group of verified interactions [36]. The initial block is called a genesis block which has no previous block as shown in Fig. 2 . The transactional data in blockchain are permanent and cannot be altered once they are legitimately authorized by a consensus-based process and recorded into the ledger. The data updates are instantly disseminated across the chain. Hence, it enables customers to audit and verify their communications autonomously and transparently. The distributed and transparent nature of blockchain enables users to save and track transactional data efficiently. These features can also eliminate the double-spending problem [37]. Double-spending is a common fault in a crypto currency system where the same single token can be expended more than once. Also, blockchain is a trustless computing environment in which the validity of the transactional data is guaranteed without any third-party authorization [38].

Fig. 2.

Overview of blockchain technology.

Fig. 3 describes the overall structure of blockchain. The blocks contain a header and a body. The header consists of the following six fields.

• •Version (4 bytes): This field denotes which consensus protocol is to be used in the current application.
• •Previous hash code (32 bytes): It represents the hash code of the preceding block. Without this field, there is no link and chronology among logs.
• •Merkel Root: This field is employed to identify each interaction. This field is represented as a binary tree of hash values. It is used in bitcoin to make the data blocks tamper-proof.
• •Difficulty Target (4 bytes): This field calculates the target threshold of the hash value to identify the legal block.
• •Nonce (4 bytes): Nonce is a random number used for secure transactions. Generally, it starts with zero and increases gradually for each hash calculation.
• •Timestamp (4 bytes): It is given in seconds since 1/1/1970. It is used to ensure block integrity by monitoring the generation and modification time of a record securely. At this point, security means that no one (not even the proprietor of the record) should be able to alter it once it has been registered provided that the data integrity is never compromised.

Fig. 3.

General structure of a block.

The body of the block contains established and validated transactions. The transaction counter is used to count all the transactions. The state of the block denotes who transferred which data to whom at a particular time. A recognized transaction among two peers only befalls when it is involved in a block then it is certified and linked to the chain. Hence, the log must be accessible publicly. This demonstrates the inevitability of P2P networks in blockchain technology [39]. The working principle of blockchain technology when a customer sends transactional data (e.g. crypto currency) to another customer is illustrated in Fig. 4 . The following key characteristics make blockchain is superior to any other centralized database management system.

• •Decentralization: In blockchain technology, the transactions are managed and validated using decentralized records. For instance, in the crypto currency system, it is not mandatory for any reliable third party such as Bank. All peers can collaborate on all aspects for verifying and connecting blocks in the chain.
• •Persistency: It is not possible to roll back or discard a registered transaction. However, illegal transactions are identified instantly.
• •Anonymity: The user exploits virtual identity code to interact with the blockchain network. The process of virtual identification does not expose the actual user identity. Therefore, this characteristic brings numerous privacy and security issues to blockchain-based applications [40].
• •Auditability: This characteristic represents the secure connection between every block and the previous one. It makes transactional data monitored and verified easily.

Fig. 4.

Working mechanism of blockchain.

2.3. Chain of Things technology

To realize the maximum potential of the CoT network in the supply chain management system, it is essential to explore an industrial model, where blockchain technology is inherently integrated with IoT technology. Since the number of IoT expedients increasing every year, data security has become more difficult. Blockchain is used to evade these security issues and single-point failures to achieve reliable device communications in an IoT network. CoT leverages several potential reimbursements of blockchain and IoT technologies and plays a central role in tracking, controlling, and mainly securing smart things. It allows a peer device to operate independently without the intervention of trusted third parties and monitor how peers interact with each other.

Fig. 5 depicts the top five predictions of CoT for 2030 [41]. Based on these predictions, by 2030, most countries will adopt or create different digital currencies in most (perhaps all) of their commercial transactions. In the future CoT era, trillion-dollar tokens will act a vital role in enhancing the flow of the digital economy. CoT enables frictionless transactions of tokens and other resources. By 2030 or even earlier, all individuals and their virtual/physical resources will have blockchain identities. CoT will help enhance systems for handling those identities locally as well as globally through several identity solutions. By 2030, noteworthy signs of progress in the quality of life will be attributable to the emerging CoT network. It is also predicted that most of the world's business will be carried out through CoT technology.

Fig. 5.

Top Five predictions.

2.4. The indispensable links between CoT and HSC

CoT technology has benefits for comprehensive HSC networks, such as enabling powerful data sharing, credibility, logging of past dealings in smart things, monitoring system performance, transferring distributed files, providing lucrative Internet services, and speeding up trades. In addition, CoT technology can guarantee the high quality and originality of the products and tempt the user to purchase the products. CoT increases the traceability and transparency of the HSC by utilizing immutable data, controlled access, and decentralized reserves for customers. CoT research has discussed in what way we can precisely monitor and handle billions of interconnected smart things, how to handle big data engendered by IoT network and how to perform all of these processes securely and safely. This distributed technology minimizes the probability of network failure and builds a more resilient supply chain for the healthcare sector. Also, the encryption techniques employed in CoT maintain data confidentiality. Hence, the acceptance of CoT in HSC can address its inherent problems, in a way that is employed to monitor billions of interconnected things, execute instructions and facilitate cooperation among devices. The links between CoT and HS Care likely to be influenced by many features: (i) decentralization – CoT acts an important role to solve security and privacy issues in the HSC management system; (ii) persistency - CoT provides a persistent and comprehensive solution for the healthcare sector; (iii) powerful transaction -CoT becomes prevalent for payment systems in HSC that exclude the demand for trusted third party, like a bank; (iv) tracking and identification - smart contracts of CoT allows for better tracking of healthcare products; and (v) real-time analysis - CoT improves real-time sovereign and secure payment services, improves conventional commerce, e-commerce or private and public conveyance systems in HSC. In the future, CoT can be unswervingly connected to a bank account using virtual currency to make micro-transactions for services and analogous methods may be employed in the HSC management system.

3. Key lessons learned from COVID-19

Although the viral pandemic marks a huge dent in the economy and financial markets on a global scale, it brings some significant insights into how HSC can be made more reliable and how industries figure out solutions to handle disruptions or pandemics. Every medical industry should take time to respond to pandemic challenges and then reform its business strategies to better prepare for future disruptions. While there are innumerable experiences learned from this crisis, this study confines its observation to five important areas to analyze including building a resilient supply chain, thinking localization, implementing reliable reverse logistics, realizing end-to-end visibility by breaking down silos and redesigning the supply chain using digitalization to make the most vital and immediate HSC enhancements.

Indeed, healthcare supply resilience, localization, reverse logistics, end-to-end visibility, and digitization (RLRED) have evolved early and continued as omnipresent concerns during the pandemic. The early phases of the pandemic have discovered the fragility and weakness of several supply networks worldwide, including but not limited to inadequate healthcare devices and supplies disputes. Later, CoT offers dependable RLRED solutions by providing great opportunities for competitiveness and resilience (stock availability). Fig. 6 illustrates the RLRED outcomes for adopting CoT.

Fig. 6.

Top five HSC lessons learned from pandemic.

3.1. Building a resilient supply chain

The corona pandemic opens an opportunity window for commercial transformation [42] and a more resilient supply network as well as an efficient manufacturing system [43]. In the business context, resilience is the potential of an organization to get back from a large disruption—this includes, for example, the speed at which it comes back to normal performance levels (manufacturing, fill rate, services, etc.). This pandemic creates a scope for emerging a resilient production scheme to preserve the socio-economic sustainability of the manufacturing processes. Similarly, building a more flexible supply network is mandatory to handle the pandemic or other disruptions [44]. Due to COVID-19 forced lockdowns, shortage of consumer staples, and delivery deferrals are witnessed in the downward supply chain, leading to poor performance regarding production, supply, and profits. In the chorus, it creates a surging demand for healthcare products like masks, gloves, face shields, sanitizers, and ventilators. However, many leading industries are fairly resilient enough to change their manufacturing plan to produce contagion-oriented supplies. Table 1 displays the resilience and business support of famous manufacturing industries to mitigate the impact of the pandemic.

Table 1.

Resilience of manufacturing industries during pandemic [8,45,46]).

Companies	Industry	Manufacturing products
		Pre-pandemic period	During pandemic
Tesla	Automobile	Automobiles and PV cells	Ventilators
Airbus	Aviation	Aircrafts	Ventilators
Ford	Automobile	Automobiles	Ventilators and respirator
Dyson	Technology	Vacuum cleaners and heaters	Ventilators
Bacardi	Liquor	Rum	Sanitizers
Zara	Fashion	Apparels	Surgical Masks
Gucci	Fashion	Clothing	Masks
Indian Ordnance Factories	Defence	Arms and Ammunition	Ventilators
L'Oreal	Consumer goods	Cosmetics, hair care, and perfume	Disinfectants and sanitizers

In the current business setting, HSC leaders continuously appraise their plans and tactical positions for revamping manufacturing strategy and addressing the surge in critical supply-demand. Healthcare organizations can build a resilient supply chain in three main ways.

• •Creating redundancy: The supply network with sufficient resilience can be fabricated by making redundancies across the entire supply chain [47]. The healthcare organization can have additional inventory, more dealers, preserve low capacity utilization, etc. Though redundancy can offer some breathing room to carry on the operation after a disruption, naturally it is a transitory and costly solution. The organization must pay for the additional stock, capacity, and employees; also, such redundancies are likely to cause sloppy operations, deprived quality, and considerably increased cost.
• •Creating flexibility: When an organization improves the flexibility of HSC, it can tolerate substantial disruptions and serve consumer needs effectively. To achieve flexibility in HSC, the organization should take the following actions: (i) implementing standardized processes, similar and even the same manufacturing strategies, and cross-functional integration for manufacturing basic parts in various products; (ii) employing parallel rather than serial activities (using concurrent methods in designing, manufacturing, and distribution of products accelerates the recovery phase after a disruption and offers collateral reimbursements in enhanced market responses); and (iii) aligning procurement plan with distributor relationships to identify potential issues and rely on them for managing unpredictable situations.
• •Conducting risk analysis: In response to the crisis, healthcare providers have struggled to stabilize their HSC by performing risk assessments and executing business continuity strategies.

3.2. Thinking localization

The most important lesson learned from the pandemic is localization. Due to government-imposed shutdowns, the demand for essentials and healthcare products is immediately apparent. Local industries, especially small-scale industries, stood up to fulfil demands in local trade. During a pandemic, scarcities in healthcare products have demonstrated that the existing global HSC is extremely onerous and frequently vain [48]. Localization is the task of internalizing managerial tasks and partial in sourcing activities that were completely externalized previously [45]. Besides, it is a business strategy intended to supply critical facilities or goods using domestic supply networks [49]. Increasing local production, employment, and investment, scheming and protecting patented technology, decreasing unforeseen outsourcing costs, and alleviating risks are the important enablers of HSC localization. Organizations implement localization policies for production and supply chain processes to reduce distance-oriented risks [45,50]. Since global HSC sourcing is challenged, localized sourcing became more imperative. In the pandemic situation, the necessity for local manufacturing has arisen due to health, business, and political reasons. For instance, as the corona virus instigated, the United States banned importing materials and goods from China. Health and commercial distress involved the potential concern of spreading the infection via wrapping, products, and travel by the public of both nations.

Localization increases the resilience of the supply chain and it can be achieved by in sourcing or reshoring processes. It adds more flexibility to the existing supply network since distances are shorter and the products are delivered by local partners. Though the possibility of localization becomes bounded in terms of the availability of resources/materials for sourcing and refill, it manages local wastes and produces new items that can be reproduced, recycled, renovated, or recovered, and effectively distributed locally. For example, Amazon's managers must understand localization policies, and looking for business associates in their locality as inter-coiled producers/distributors is an efficient way to manage logistics [51] and processes such as recovery, recycling, and reuse [52]. Local partners are responsive and flexible. They supply local customers more rapidly than global supply chain partners. Co-governmental activity is one more example of localization in which private organizations and governments collaborate in their local areas. For instance, in Massachusetts, United States, an effort directed by the state government, academic institutions, and industries collaborated to deliver the required PPE to frontline healthcare workers quickly.

3.3. Implementing reliable reverse logistics

Since distributors steer operational and supply chain interruption aggravated by the pandemic, different reverse logistics issues arise, and conventional pain points increase. To recover and prosper now and in the future, distributors must identify feebleness in their reverse logistic policies to better protect properties and revenues while meeting the fluctuating demands of users. Generally, reverse logistics represents the pool of retrieving goods in gathering stations and their flow from downward to upward supply chain [53]. The key objective of reverse logistics is to increase the sustainability of the supply network by alleviating adverse ecological effects [54]. The COVID-19 has raised the significance of reverse logistics, as suppliers deal with intensifying inventory turn and functional costs globally. The pandemic reveals prevailing weaknesses in reverse logistics activities, demanding industries to focus on their crucial pain points to recover and prosper in the new normal. The pandemic has triggered a surging demand for telemedicine facilities, as the pandemic has urged calls for more widespread application of telemedicine [55]. For example, in China, the development of online healthcare services has considerably boosted [56]. During the pandemic, several healthcare organizations exhibited three-digit progress. Some healthcare organizations are intensifying their processes to help their customers benefit from a wide range of healthcare facilities, and few authorities are revising acts and guidelines to enable tele-health facilities, mostly temporarily. Product makers or reverse logistics enterprises need to manage the arrival of replaced or returned products in a crisis.

Prior to the onset of the pandemic, the leap of online returns exceeded in-store returns by 30%. Due to lockdowns, there has been an interruption in reverse logistics. Numerous customers have held back their products, waiting for the reopening of supply networks. This interruption led to chaos when the supply chain instigates as constraints on lockdown let up. To proficiently handle the torrent of returns, distributors must implement the techniques they use in the holiday season. Warehouse owners and distributors can implement data-driven approaches that can scan and analyze the returned products. According to the data points, proprietors can find out what must be done with these items. If it is found that products can be renovated and sold again, it will decrease the waste and increase productivity. There are concerns over cleaning and sanitizing of these products to avert contagion as it is observed that the virus can be alive on surfaces for hours and days. Safety guidelines and recommendations by governments must be followed and measures must be established in view of that. There has been a reallocation of employees from stores to warehouses for managing those products effectively. Since several employees have been unwilling to return to work, suppliers must establish safety measures and train employees on safety practices.

3.4. Breaking down existing silos to achieve end-to-end visibility

The pandemic uncovered numerous weaknesses in HSC, including a deficiency of synchronized data sharing. The pandemic also exposed that it is critical for each stakeholder in the HSC to determine methods to share information, interact efficiently, and work cooperatively to guarantee that care providers get the drugs/devices they need to serve patients. Progressive organizations are leveraging HSC technology to support data sharing and foster partnership between drugs/device producers, suppliers, pharmacies, hospitals, and other partners in the HSC. This takes account of digital tools intended to break down silos among stakeholders and coordinate positive patient outcomes. Organizations are now implementing novel and advanced HSC approaches to increase visibility, reform HSC management, and realize higher levels of cooperation with trading partners to form a more reliable and resilient HSC.

By assimilating all data from the entire supply chain into a solo foundation, the HSC accomplishes a comprehensive view. This end-to-end visibility provides better insights into multipart activities. Counterfeit drug production creates trades that exceed $200 billion yearly, making it the most profitable illegal business. It leads to shocking destruction in the lives of individuals while destroying confidence in the brand's integrity. The complete insight from HSC supports medicinal producers to avoid deviation and forging through product monitoring. End-to-end visibility also aids to provide delivery transparency. The various departments of an organization can collect the data to track the particular batch, how new orders are being managed, and the speed of freight.

3.5. Redesigning HSC using digitalization

Once the global pandemic emerged, the leap of technological change in the HSC was promoted dramatically. Overnight, healthcare manufacturers/suppliers were contending with completely different challenges. Organizations that were exploiting outdated visibility and predicting techniques (e.g., worksheets, independent software, etc.) had difficulties with the surge in e-commerce orders, handling remote labour force, managing supply disruptions, and fulfilling fluctuating user demands. In the pandemic, customers have shifted vividly to online shopping, and organizations have responded accordingly and communicated with consumers via digital networks. The interruption has utterly promoted the interest in building digital business models. As new supply-oriented devices, applications, and software hit the market, suppliers across all industries have been analysing those tools and implementing them into their supply chain policies.

The COVID-19 pandemic has enabled industries and people to enhance virtual partnerships as a cost-effective alternative for travel and face-to-face gatherings. Digitalization is defined as the fundamental logic for quarantine and social distancing efforts to preserve chunks of the financial system, support online procurements, and enable socialization [57]. Digitalization of an HSC provides enhanced communication, regulated data flow, and improved resource utilization in healthcare industries [58]. Digitalization of HSC increases access to customer information and market demand. Through a digital supply network, healthcare manufacturers can establish strong relationships with their suppliers. It improves the visibility of HSC and enables suppliers to develop strategic relationships among existing supply chain partners, and reveals possibilities to collaborate with the new partners. Also, the scope of items can be stretched and the design complication of the process analysed through modern technologies. Also, the pandemic has exposed the restrictions of market uncertainties and the human workforce. At present, organizations are on their track to accelerate the implementation of the digital supply network and one can expect to realize a significant pace in its operations. Even after the economy bounce back from this crisis, digital HSC will allow companies to manage huge data for making updated strategic decisions. In addition, the reduction in the physical handling of products will also increase sanitization in workstations.

3.6. Learnings

In the event of a pandemic, managing the resilient HSC is a difficult endeavour for industry managers and healthcare providers. Here, the authors put their perspective to increase the performance of delivery of healthcare products and facilities. The organizations and service providers would be benefited from the following recommendations.

• •The key objectives of resilient HSC include decreasing supply chain risks and making the healthcare industry rapidly respond and bounce back from such interruptions.
• •A robust and reliable integration is required among participants of HSC including manufacturers, suppliers, healthcare organizations, physicians and end-users, and probably the government to better tackle the crisis.
• •Existing manufacturing practices should transform to Industry 4.0 (i.e., digital manufacturing), and exploit the modern tools (e.g., industrial automation, IoT, blockchain, AI, robotics, 3D printing, etc.) for product manufacturing.
• •The pandemic makes fluctuations in the ingestion of pharmaceuticals and medical equipment. Hence, industry managers should consider the fluctuating demand for particular products in this situation.
• •In addition to reduced cost, inventories, and improved resource utilization, it is a chance for healthcare manufacturers to shift to digital supply networks from the conventional supply chain. These networks aid to provide a unique identity for medical items, complete visibility, partnership, agility, responsiveness, reliable logistics, and a resilient supply chain.
• •Design HSC appropriate for alternate sourcing for suppliers, logistics service providers, and raw materials to handle pandemic interruptions.
• •Establish more resilient shipping and supply networks to satisfy the intensified manufacturing and consumer demand.
• •Though the pandemic helps in increasing the resilience of the HSC, it is not sufficient to handle the new normal business opportunities. The policymakers and researchers should build resilient HSC to consider safety practices and social health now and post-pandemic world.

4. Fuzzy DEMATEL analysis

This study aims to reveal the influence path of CoT on smart HSC development using the DEMATEL method. DEMATEL is a multi-criteria decision-making method to analyze the correlation among factors using cause-effect analysis. The DEMATEL is an efficient method for identifying influencing factors. More precisely, it helps to handle the complex relationships among designated features. But, only the DEMATEL technique is not well equipped to solve the potential uncertainty and fuzziness in the data [59]. Hence, this work integrates fuzzy set theory and DEMATEL methods to develop F-DEMATEL in order to assess the interconnection between features and reveal the correlation among various hierarchies, disclosing the influence path of CoT on the HSC system. In this study, the lessons learned from the pandemic as well as major attributes of CoT have been collected by literature review and by interrogating experts through opinion polls. The fuzzy approach determines the uncertainties and complications related to the data. The fuzzy triangular scale (FTS) can convert linguistic variables (i.e., expert preferences) into numerical values to find out the relative importance of the features. In this work, FTS is used to determine the pair wise contributions.

The conventional DEMATEL method employs exact numerical values to characterize the complex correlation between features, which sometimes cannot completely reveal the exact condition of the problem. To handle this problem, this study introduces the idea of FTS for implementing the traditional DEMATEL technique. Thus, this method upturns the dependability of the system and becomes a more beneficial reference base for industry people to make appropriate decisions. Before implementing the DEMATEL method, the important features are identified on the basis of literature review and analysis. This work summarizes 13 factors influencing CoT-based HSC. From June to September 2021, this study selects12 persons who have more than 8 years of experience in the field of HSC, IoT, and blockchain as our interviewees. The authors carried out a field survey to assess the mutual influence of these 13 factors through direct interviews. This work reviewed and summarized the expert's responses to calculate the fuzzy direct impact matrix of the influential features of CoT technology in the HSC system. Then, the authors calculates the comprehensive impact matrix using MATLAB. F-DEMATEL algorithm employed in this work follows the steps given below.

• Step 1: Before implementing the DEMATEL approach the features are labelled as given in Table 2. According to the literature review carried out in this study and the opinion of experts, the features can be selected as follows.

• •Features of HSC (resilience, localization, reverse logistics, end-to-end visibility, digitization)
• •Features of CoT (decentralization, persistency, anonymity, auditability, powerful transaction, tracking and identification, real-time analysis, authentication)

• Step 2:F-DEMATEL considers the expert scoring to find out the connection between a pair of features. This study develops an expert evaluation semantic scale using FTS and divides the degree of influence among features into 5 levels. Table 3 shows the specific degree of influence.

Table 2.

Variable coding.

HSC features	CoT features
S1: Resilience	S6: Decentralization	S10: Powerful transaction
S2: Localization	S7: Persistency	S11: Tracking and identification
S3: Reverse logistics	S8: Anonymity	S12: Real-time analysis
S4: End-to-end visibility	S9: Auditability	S13: Authentication
S5: Digitization

Table 3.

Semantic translation.

Linguistic variables	FTS
Extremely Important	(0.8, 1.0, 1.0)
Strongly Important	(0.4, 0.6, 0.8)
Fairly important	(0.2, 0.4, 0.6)
Weakly important	(0.0, 0.2, 0.4)
Not important	(0.0, 0.0, 0.2)

The DEMATEL questionnaire was completed by 10 specialists including industry managers and academic people. The selected people are specialists in the domain of healthcare supply chain and CoT as given in Table 4 .

• Step 3:For converting fuzzy data into the crisp scores, this study constructs the triangle fuzzy matrix and the direct influence matrix for the selected features. The calculation process of the crisp scores method is as follows:

• (i)Standardization of FTS

$${xs}_{1,ij}^k=\frac{s_{1,ij}^k-\mathit{min}{s}_{1,ij}^k}{{\Delta }_{\mathit{min}}^{\mathit{max}}}$$ (1)

$${xs}_{2,ij}^k=\frac{s_{2,ij}^k-\mathit{min}{s}_{1,ij}^k}{{\Delta }_{\mathit{min}}^{\mathit{max}}}$$ (2)

$${xs}_{3,ij}^k=\frac{s_{3,ij}^k-\mathit{min}{s}_{1,ij}^k}{{\Delta }_{\mathit{min}}^{\mathit{max}}}$$ (3)

• (ii)Standardize the left-hand side and right-hand side

$${xls}_{2,ij}^k=\frac{{xs}_{2,ij}^k}{\left(1+{xs}_{2,ij}^k-{xs}_{1,ij}^k\right)}$$ (4)

$${xrs}_{2,ij}^k=\frac{{xs}_{3,ij}^k}{\left(1+{xs}_{3,ij}^k-{xs}_{2,ij}^k\right)}$$ (5)

• (iii)Compute the clear value of each expert's score after it is blurred

$$x_{ij}^k=\frac{{[xls}_{ij}^k\left(1-{xls}_{ij}^k\right)+{xrs}_{ij}^k{xrs}_{ij}^k]}{\left(1-{xls}_{ij}^k+{xrs}_{ij}^k\right)}$$ (6)

$$z_{ij}^k=\min s_{1,ij}^k+x_{ij}^k{\Delta }_{\mathit{min}}^{\mathit{max}}$$ (7)

• (iv)Compute the average clarity value

$$z_{ij}^k=\frac{\left(z_{ij}^1+z_{ij}^2+\dots z_{ij}^k\right)}{n}$$ (8)

• Step 4:The direct influence matrix z is standardized as given below.

$$\lambda =\frac{1}{{\mathit{max}}_{1\le i\le n}\sum _{j=1}^n{z}_{ij}}$$ (9)

$$G=\lambda z$$ (10)

Step 5

Calculate the composite impact matrix $T=G{\left(E-G\right)}^{-1}$ using MATLAB, where E is the constant matrix.

Step 6

The degree of impact and being impacted are calculated by adding each row and each column of the composite impact matrix. This study computes the dispatcher (D) by adding each row to indicate the order of features that strongly impact other features, and calculate the receiver (R) by adding each column to indicate the order of the features that are influenced.

$$D_i=\sum _{j=1}^n{t}_{ij}$$ (10a)

$$R_i=\sum _{i=1}^n{t}_{ij}$$ (11)

The sum of the dispatcher and receiver is known as centrality ($m_i)$, demonstrating the role of elements in the system. It designates the extent to which the anticipated feature influences or gets influenced in the system, and the larger it is, the more interaction with other features and the more significance it has. The difference between the dispatcher and the receiver is known as causality $\left(n_i\right)$. It reflects the influence power of each feature. Generally, $m_i>0$ indicates that the factor is “cause” otherwise (i.e., $m_i<0)$, the factor is “effect”. The value of centrality and causality are calculated as follows:

$$m_i=D_i+R_i,i=1,2,\dots n$$ (12)

$$n_i=D_i-R_i$$ (13)

$$H=T_i-R_i$$ (14)

Now, the direct influence matrix is computed to get an all-inclusive relationship among the factors. A comprehensive influence matrix (T) reveals only the mutual influence relationship and degree among various features, without considering the impact of features on themselves. Therefore, computing the complete influence relationship of features is important.

$$h_{ij}=T+E$$ (15)

$$\lambda =\sigma +\rho$$ (16)

where $\sigma$ and $\rho$ are the mean and standard deviation of all factors in the comprehensive influence matrix T, respectively. The reachable matrix is calculated as given below.

$$M={\left[m_{ij}\right]}_{n\times n}$$ (17)

where i = 1,2,3 … n; and j = 1,2,3 … n.

$$m_{ij}=\{\begin{array}{c}1,h>\lambda \\ 0,h<\lambda \end{array}$$ (18)

If there is a correlation between elements i and j, then the value is 1 (i.e., reachable); or else, it is 0 (i.e., not reachable).

This study carried out a field survey to assess the mutual influence of these 13 factors through direct interviews. The fuzzy direct impact matrix of the influential parameters of CoT technology in the HSC system are estimated using F-DEMATEL method and the results are listed in Table 5 .

Equations 10–14 can be employed to calculate the value of the influence degree, affected degree, centrality, and causality, and the results are listed in Table 6 . The selected features are divided into a cause set and a result set based on the value of causality, and it is shown in Table 7 . There are 7influential factors, including S11 (Tracking and identification), S8 (Anonymity), S4 (End-to-end visibility), S2 (Localization), S3 (Reverse logistics), S9 (Auditability), and S6 (Decentralization) considered in this work. Among them, S11 (Tracking and identification), S8 (Anonymity), S4 (End-to-end visibility), and S2 (Localization) are the main motivations. The influence degree of S11, S8, S4, and S2, is 3.079, 2.966, 3.186, and 3.105, correspondingly, which are the most influential factors, manifesting that these three factors have the greatest impact on other factors. This is because tracking and identification, anonymity, end-to-end visibility, and localization are the roots of the impact of CoT on HSC. There are three result elements, including S3 (Reverse logistics), S9 (Auditability), and S6 (Decentralization), which have little impact on HSC but are more susceptible to other factors. So, in management practices, these factors should be taken into account and placed under appropriate control to improve management effectiveness.

For centrality, these factors follow the order of S11 tracking and identification (5.886), S8 anonymity (4.698), S4 end-to-end visibility (4.668), S2 localization (4.335), S7 persistency (3.840), S13 authentication (3.682), S3 reverse logistics (3.621), S1 resilience (3.537), S9 Auditability (3.424), S5 digitization(3.377), S6 decentralization (3.259), S10 powerful transaction (2.959), and S12 real-time analysis (2.746).The reachable matrix obtained from Equation (18) is shown in Table 7. From this table, it is observed that S2 (localization), S3 (reverse logistics), S4 (end-to-end visibility), S6 (decentralization), S8 (anonymity), S9 (auditability), and S11 (tracking and identification) are causes. Similarly, S1 (resilience), S5 (digitization), S7 (persistency), S10 (powerful transaction), S12 (real-time analysis), and S13 (authentication) are called effects. The reachable matrix obtained from Equation (18) is shown in Table 8 .

From this analysis, it can be concluded that tracking and identification, anonymity, end-to-end visibility, and localization are the first elements that CoT influences the HSC system, and the key is to find out how to track and control these features in real-time. To sum up, the parameters prompting the application of CoT in the sustainable development of HSC are difficult. On the other hand, the mechanism of influence, method of influence, and degree of action diverge based on the features, so technology integration, as well as scientific application models are indispensable for building sustainable HSC.

Table 4.

Participants in Dematel method and structural interpretive modelling.

Participants	Designation	Respondents
Academic people	Faculty	5
Industry people	Senior manager	4
	Project manager	3

Table 5.

The direct influence matrix of CoT technology on HSC.

	S1	S2	S3	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13
S1	0.000	0.169	0.017	0.169	0.683	0.017	0.017	0.169	0.017	0.683	0.169	0.017	0.683
S2	0.017	0.000	0.436	0.493	0.416	0.360	0.436	0.417	0.550	0.321	0.417	0.436	0.416
S3	0.569	0.455	0.000	0.131	0.436	0.055	0.455	0.283	0.302	0.207	0.283	0.455	0.436
S4	0.302	0.131	0.569	0.000	0.302	0.226	0.569	0.417	0.570	0.207	0.017	0.569	0.302
S5	0.017	0.055	0.017	0.017	0.000	0.017	0.017	0.074	0.017	0.017	0.074	0.017	0.074
S6	0.474	0.131	0.074	0.226	0.493	0.000	0.074	0.245	0.226	0.436	0.226	0.550	0.493
S7	0.550	0.245	0.417	0.074	0.017	0.112	0.000	0.264	0.017	0.226	0.417	0.302	0.131
S8	0.245	0.455	0.436	0.493	0.245	0.455	0.417	0.000	0.493	0.302	0.074	0.570	0.017
S9	0.017	0.131	0.017	0.131	0.398	0.683	0.169	0.131	0.000	0.436	0.245	0.017	0.131
S10	0.569	0.055	0.017	0.017	0.017	0.017	0.017	0.074	0.017	0.000	0.264	0.226	0.226
S11	0.131	0.245	0.074	0.131	0.493	0.455	0.417	0.264	0.226	0.436	0.000	0.017	0.074
S12	0.017	0.131	0.569	0.226	0.416	0.226	0.569	0.417	0.570	0.321	0.417	0.000	0.570
S13	0.550	0.245	0.417	0.074	0.017	0.112	0.074	0.245	0.226	0.436	0.226	0.493	0.000

Table 6.

The comprehensive impact matrix of CoT on HSC.

	S1	S2	S3	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13
S1	0.044	0.086	0.048	0.084	0.241	0.043	0.050	0.091	0.047	0.236	0.241	0.050	0.091
S2	0.188	0.119	0.239	0.239	0.304	0.219	0.250	0.238	0.252	0.265	0.304	0.250	0.238
S3	0.238	0.102	0.073	0.102	0.234	0.073	0.188	0.149	0.065	0.203	0.234	0.188	0.149
S4	0.268	0.126	0.277	0.15	0.296	0.191	0.287	0.246	0.260	0.256	0.296	0.287	0.246
S5	0.018	0.025	0.016	0.016	0.017	0.016	0.173	0.031	0.016	0.021	0.017	0.173	0.031
S6	0.198	0.129	0.086	0.123	0.241	0.057	0.089	0.135	0.068	0.217	0.241	0.089	0.135
S7	0.238	0.104	0.175	0.112	0.187	0.091	0.077	0.145	0.085	0.179	0.187	0.077	0.145
S8	0.248	0.127	0.244	0.247	0.278	0.243	0.250	0.141	0.243	0.276	0.278	0.250	0.141
S9	0.243	0.107	0.069	0.104	0.239	0.238	0.108	0.113	0.055	0.241	0.239	0.108	0.108
S10	0.018	0.025	0.017	0.016	0.216	0.016	0.017	0.031	0.017	0.015	0.216	0.017	0.017
S11	0.268	0.126	0.277	0.15	0.296	0.191	0.287	0.246	0.260	0.108	0.296	0.287	0.287
S12	0.018	0.025	0.016	0.016	0.017	0.016	0.173	0.031	0.016	0.017	0.017	0.173	0.173
S13	0.198	0.129	0.086	0.123	0.241	0.057	0.089	0.135	0.068	0.287	0.241	0.089	0.089

Table 7.

Comprehensive impact matrix analysis.

Factor	Influence degree	Affected degree	Centrality	Causality
S1	1.352	2.185	3.537	−0.833
S2	3.105	1.230	4.335	1.875
S3	1.998	1.623	3.621	0.375
S4	3.186	1.482	4.668	1.704
S5	0.570	2.807	3.377	−2.237
S6	1.808	1.451	3.259	0.357
S7	1.802	2.038	3.840	−0.236
S8	2.966	1.732	4.698	1.234
S9	1.972	1.452	3.424	0.520
S10	0.638	2.321	2.959	−1.683
S11	3.079	2.807	5.886	0.272
S12	0.708	2.038	2.746	−1.330
S13	1.832	1.850	3.682	−0.018

Table 8.

Reachable matrix.

	S1	S2	S3	S4	S5	S6	S7	S8	S9	S10	S11	S12	S13
S1	1	0	0	1	1	1	0	0	0	1	1	0	0
S2	0	1	1	0	1	1	0	1	1	1	1	1	1
S3	1	0	1	1	1	1	0	0	0	0	1	1	0
S4	1	1	1	0	0	0	0	1	1	1	0	1	1
S5	1	0	0	1	0	0	1	0	0	0	0	1	0
S6	1	0	0	0	1	1	1	0	0	0	1	0	0
S7	0	0	0	0	0	0	0	0	0	0	0	0	0
S8	1	1	1	0	0	0	1	1	1	1	0	0	1
S9	0	0	0	1	0	0	0	0	1	1	0	1	0
S10	0	0	0	0	0	0	0	0	0	1	0	0	0
S11	1	1	1	0	1	0	1	1	0	0	0	0	1
S12	0	0	0	1	0	0	0	1	0	1	0	1	0
S13	1	0	1	1	0	1	1	0	1	0	1	1	0

5. Proposed healthcare supply network using CoT

The crisis has uncovered the primary intricacies and weaknesses of global supply networks and demonstrated the significance of a well-functioning HSC. At present, HSC networks are unable to handle the issues related to safety and transparency, and realize the ethical demands imposed by the regulatory bodies. As extant ICTs fail to handle these issues, CoT technology is developing as an efficient and secure solution. When integrated, Blockchain and IoT technologies have the potential to enhance the performance and effectiveness of HSC. IoT can increase the resilience of the HSC by implementing an efficient method for monitoring the delivery of materials or products. This leads to enhancements in the performance and productivity of critical operations and time schedules [60]. Furthermore, IoT enables the stakeholders to help in disseminating more accurate and real-time data associated with product manufacturing, quality assurance, supply, and logistics.

In spite of the increasing possibility to implement IoT technology in HSC, there are many technical issues ahead including privacy, confidentiality, authenticity, and security of all participants [61]. From a vulnerability viewpoint, researchers and practitioners consider security to be the most important concern [62,63]. Prevailing security solutions are not appropriate since existing smart things may dissipate considerable amounts of power and may have substantial computational complexity [63]. Furthermore, issues including physical tampering, counterfeiting, data theft, and hacking might increase trust concerns amongst HSC stakeholders [64]. Hence, in the HSC management system, IoT must be protected against cyber attacks, and data breaches, secure the data aggregation and provide explicit assurances that the authorized users only can retrieve or alter data.

Today, blockchain technology provides several potential solutions to resolve security-related issues in IoT networks. By exploiting blockchain, healthcare organizations aim to increase data security and transparency in their HSC while facilitating collaboration between the stakeholders. Accordingly, it has attracted several researchers, healthcare organizations, and software designers who target assimilating IoT with other technologies to develop resilient HSC [65,66]. Nowadays, HSCs are experiencing a leap of transformation through unremitting digitalization. HSCs are inflowing into value-creating networks in which the value chain is acting as a foundation of fiscal benefit. In the chorus, developments are ongoing to combine IoT and blockchain technology, resulting in new configurations‚ new methods of partnerships, and value creation across healthcare supply networks [67].

To manage and monitor a CoT-based supply network, a superior model for handling data flows, and sensing the activities and communications among IoT expedients is required. The CoT-based HSC model should be flexible enough to provide a monitoring pattern for different IoT transactions. Also, it enables an effective and scalable solution for track-and-trace applications of medical products. Blockchain technology offers a secured and distributed method to share transactional data while facilitating the authentication of reliable transactions among stakeholders. The advantages of exploiting blockchain to secure IoT interactions are creating trust, decreasing cost, and fast-tracking interactions. The configuration and standards used in a CoT-based supply network can improve data security as well as enhance background processes. Also, it resolves issues in product traceability, expiration, scarcities, recalls, and counterfeits controlling in the HSC. The concept of the proposed model with medical items and IoT devices is illustrated in Fig. 7 . The devices are fortified with sensors and have connectivity to the blockchain network through the internet. This enables remote controlling, monitoring, and management of the components of HSC to deliver medical products and pharmaceuticals to the users.

Fig. 7.

Proposed CoT-based monitoring framework.

The proposed monitoring framework contains (i) a track-and-trace agent which is embedded with each IoT entity; (ii) a decentralized application (Dapp) to read the log generated by the transaction process; (iii) a log collection engine that collects and processes the data streams from IoT entities; (iv) the elastic nodes cluster that processes huge records to collate and index it into corresponding archives. The data files are distributed and registered as copies; and (v) a visualization tool that accepts the transactional data organized by node cluster and gives valuable implications of the blockchain network and nodes. Implementing the CoT as a design base for handling and tracking transactional data provides (i) more control in the throughput and performance of the HSC; (ii) transparent and end-to-end visibility; and (iii) tracking procedures to enable every node and also provide a shared network model.

In the CoT paradigm, it is required to identify the appropriate design pattern where the transactions take place. The transaction may occur in two simple ways such as communication between devices and interaction between the blockchain network and an IoT device. To enable interaction among two smart things, the blockchain network only facilitates the storage mechanism. In this design pattern, a blockchain network is used for enabling security and trust in HSC. Few data bytes are stored in the blockchain while the transactions befall outside the blockchain. This pattern is useful in scenarios in which the IoT transactions are scheduled with lower latency. Fig. 8 illustrates how two IoT trucks are interacting through a central hub which enables the things to store data in the blockchain.

Fig. 8.

A design pattern for a device to device connectivity.

To enable communication between IoT smart things and blockchain, all the transactional data are distributed through the blockchain network. Here, blockchain technology not only provides a data storage mechanism but also manages and monitors the transactions. This pattern ensures that all interactions are visible and secured. Additionally, it upturns the sovereignty of peers so that they can communicate directly with the blockchain. This communication pattern is more efficient when various IoT devices communicate through different domains. Nevertheless, integrating massive data volumes and transactions in blockchain will cause throughput and latency issues. Hence, scalability is one of the prominent dilemmas of CoT-based HSC. Fig. 9 illustrates the communication between different IoT devices with the blockchain network.

Fig. 9.

A design pattern for devices to blockchain network connectivity.

6. Linking RLRED and CoT technology for resilient HSC

The RLRED lessons learned from the pandemic are used for providing useful insights for healthcare organizations and increasing efficiency as well as the resilience of the supply network. CoT is an imperative digitalization enabler but can also provide resilience, localization, reliable reverse logistics, and end-to-end visibility to the HSC. Each part of the HSC can be enhanced with the CoT. Monitoring, evaluation, and controlling applications enable suppliers to improve performance and transparency in HSC. The proposed system provides the following key solutions to increase the resilience of the HSC.

• •Creating a unique identity for things: CoT is employed for allowing reliable identity management, ownership identification, and monitoring of items, devices, and facilities. The visibility and data transparency across the system are other advantages of CoT-based HSC. It has been employed for authenticating and controlling reliable communication while preserving the data integrity in decentralized devices. Every block in the CoT signifies an established interaction among two customers and making a new interaction is based on the previous block hash values. The logs are cryptographically secured and contracted by both users. The key benefit of CoT-based HSC besides security is every participant in the network tracks the transactions made by others and gathers information to calculate the degree of reliability. CoT also offers control utilities for reliable and distributed interaction in both communication patterns. Furthermore, it enables remote resource management and instantaneous authentication for IoT devices.
• •Verifying Transactions: CoT performs a vital task in implementing the verification and validation processes for devices. CoT records every IoT interaction on the decentralized log and controls those transactions in a secured way. These transactions are verified by all other authorized users proofed through a distinctive public key (PK) and global unique identifier (GUID). Therefore, it is useful in guaranteeing the verification and integrity of the interaction. In the proposed model, Blockstack is employed to validate the IoT transactions in HSC (Ourad et al., 2018). This method uses JavaScript Object Notation (JSON) Web Token (JWT) for validating interactions without any difficulty. The authentication with Blockstack needs effective collaboration between the Blockstack browser and the Dapp. The verification process can be achieved through the following steps:
• (1)For requesting new access, a customer signs in with Blockstack through the decentralized application.
• (2)The decentralized application then transfers customer sign-in details to the Redirect_To_Sign() function for handling the user request.
• (3)A new authentication request token is generated by the Redirect_To_Sign() function using the Blockstack browser.
• (4)Then, a JWT authentication response token is generated and forwarded by the browser to the Dapp.
• (5)To authenticate the received JWT authentication response token, the Dapp utilizes the function Handle_Pending_Sign().
• (6)Once authenticating the JWT token the Handle_Pending_Sign() function sends the authentication details to the decentralized application for responding to the customer request.
• (7)The decentralized application then sends the necessary data to the user for accessing the system.
• (8)The customer utilizes this data to access the system.
• •Protecting transactions: In our model, to enable secure transactions amongst smart things, this studyreplace the conventional communication protocols (e,g., extensible messaging and presence protocol (XMPP), hypertext transfer protocol (HTTP), etc.) with more secure protocols (e.g., transport layer security (TLS), datagram transport layer security (DTLS), etc.) (Kothmayr et al., 2013; Nguyen et al., 2015). On the other hand, the protocols TLS or DTLS have some downsides regarding processing time and space complexities. Also, these protocols have some glitches with central controlling authority and key management. Blockchain technology can handle these issues and improve the performance of key generation and distribution by allocating an exclusive PK and GUID pair to each thing (Khan and Salah 2018). In CoT-based HSC, new secure communication can be achieved to share PKI certificates without using any handshaking process as in TLS or DTLS protocols. Hence, CoT provides the best solution to decrease time and space complexities. Also, the firmware of the things can be hashed into a block constantly for identifying Malwares and warn the device proprietor to do the needful or auto defends against the identified cyber attack. Authentication transaction is another advantage of the CoT network. For example, the sending peer hashes a transaction that needs to send to others and inserts the hash value into a block. Then, the receiving peer hashes the message. If the hash code equals the hash code on the CoT, then the established transaction has not interfered during transit.
• •Building resilient HSC: By implementing CoT technology healthcare organizations can build more resilient HSC during and beyond the pandemic. In healthcare supply networks, building a resilient HSC that not only develops to mitigate risks but is also ready to rapidly adapt and recover from any unexpected interruptions that happen. Employing resilient HSC solutions need a completely useful and flexible infrastructure along with services that facilitate transparency and end-to-end visibility. This can enable HSC stakeholders to access all the correct data and make decisions based on real-time data produced from HSC. In a healthcare supply network, once transactional data are recorded in a block, they are visible to the entire chain. The transparency, traceability, and immutability create the provenance of the medical items across the HSC. The visibility of transactions that have many participants enables security and transparency. After data is stored in a block, it cannot be altered, guaranteeing trust and immutability. This becomes the cornerstone of a reliable HSC. With digitized monitoring systems, the stakeholders can locate their products and follow how the products are vending. The IoT technology with RFID tagging is used to locate the products, track consignment status, and protect it in a database for scheduled invoicing, reporting, and replacement without human intervention.

7. Conclusion

The pandemic has exposed numerous cracks and weaknesses in the conventional pattern of manufacturing, consumption, and their ongoing effect on healthcare supply networks. During the pandemic, the potential of digital technology initiatives in the current state of HSC systems became apparent. Recently, the CoT network has attracted extensive attention from researchers and organizations as a facilitator of significant innovation and adds a new dimension to the resilient HSC due to its exceptional features of decentralization, data sharing, persistency, anonymity, and auditability. This work is intended to explore the significance of assimilating the IoT and blockchain in emerging Chain of Things technology and its implementation in the healthcare supply network. This work identifies important features related to CoT and HSC. Also, this study links these lessons to a potential solution through CoT technology. CoT technology provides a better way to monitor HSC products by integrating the Internet of Things (IoT) with blockchain networks. However, such an integrated solution should not only focus on the required features and aspects but also on the correlation among different features. The major objective of this study is to reveal the influence path of CoT on smart HSC development. Hence, this study exploits (i) fuzzy set theory to eliminate redundant and unrelated features; (ii) the DEMATEL method to handle the intricate correlation among different features. This F-DEMATEL model attempts to direct CoT technology towards smart HSC by identifying the most influencing factors and investors are recommended to contribute to the development of application systems. From this analysis, it can be concluded that tracking and identification, anonymity, end-to-end visibility, and localization are the first elements that CoT influences the HSC system, and the key is to find out how to track and control these features in real-time. To sum up, the parameters prompting the application of CoT in the sustainable development of HSC are difficult. On the other hand, the mechanism of influence, method of influence, and degree of action diverge based on the features, so technology integration, as well as scientific application models, is indispensable for building sustainable HSC. This technological orchestration of CoT can offer new-fangled solutions for inherent security threats and performance issues related to IoT devices used in HSC.

The key findings of this work can be summarized into three major contributions. Firstly, five important supply chain lessons learned from the global pandemic to build and maintain a most efficient HSC as it returns to a new normal including building a resilient supply chain, thinking localization, implementing reliable reverse logistics, breaking down extant silos to achieve end-to-end visibility, and redesigning HSC using digitalization are identified. Secondly, this study developed a new CoT-based monitoring framework that can be employed in the healthcare supply network to build a resilient HSC. The proposed model can increase opportunities in the HSC and be employed as imperative solutions to solve key issues in the traditional HSC network. Finally, the study links the profound lessons to a potential solution through the CoT network to provide a secure way to monitor medical products. The F-DEMATEL approach is a convenient tool and extensively employed in HSC network to handle problems that require group decision-making in a fuzzy setting. However, this system has some shortcomings in the representation of paradoxes as an attribute of human intelligence. Hence, the authors intend to apply neurosophic logic to deal imprecision, vagueness, inconsistency, and ambiguity when information is logically ranked, indefinite, uncertain, and contradictory to real-world information.

Authorship statement

Conception and design of study: V. Sathiya, K. Nagalakshmi; acquisition of data: V. Sathiya, K. Nagalakshmi; analysis and/or interpretation of data: V. Sathiya, K. Nagalakshmi, Ángel Acevedo-Duque, R. Anand Babu, J. Jeevamalar, R. Karthi, R. Lavanya. Drafting the manuscript: V. Sathiya, K. Nagalakshmi, S. Ramabalan; revising the manuscript critically for important intellectual content: V. Sathiya, K. Nagalakshmi, Ángel Acevedo-Duque, R. Anand Babu, J. Jeevamalar, R. Karthi, R. Lavanya, S. Ramabalan; Approval of the version of the manuscript to be published (the names of all authors must be listed): V. Sathiya, K. Nagalakshmi, Ángel Acevedo-Duque, R. Anand Babu, J. Jeevamalar, R. Karthi, R. Lavanya, S. Ramabalan.

Biographies

V. Sathiya received her B.E. (Electronics and Communication Engg.) from Madras University, Chennai. She received her M.E. (Computer and Communication) from Anna University, Coimbatore. Also she completed her Ph.D in Anna University, Chennai. She is working as a faculty in Department of Electronics and Communication Engg., E.G.S. Pillay Engineering College, Nagapattinam, India. Her research interests are Optimization techniques, Robotics and Communication devices. Corresponding author. Email: sathiyav2105@gmail.com

K. Nagalakshmi is working as a faculty in Department of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, India. Her research interests are IOT, Black chain, Computer Science, etc.

Ángel Acevedo-Duque is working as a faculty in Faculty of Administration and Business Observatory of Public Policies, Universidad Autonoma de Chile, Chile. His research interests are supply chain management, Decision making strategies, Business policies, etc.

R. Anand Babu is working as a faculty in Department of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, India. His research interests are IOT, Black chain, Computer Science, etc.

Dr. J. Jeevamalar is working as a faculty in Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, India. Her research interests are Manufacturing Engg., Supply chain, IOT, etc.

Dr. R. Karthi is working as a faculty in Department of MBA, E.G.S. Pillay Engineering College, Nagapattinam, India. His research interests are Supply chain, IOT, etc.

R. Lavanya is working as a faculty in Department of Information Technology, E.G.S. Pillay Engineering College, Nagapattinam, India. Her research interests are IOT, Black chain, Computer Science, etc.

Dr. S. Ramabalan is working as a faculty in Department of Mechanical Engineering, E.G.S. Pillay Engineering College, Nagapattinam, India. His research interests are Robotics, Manufacturing Engg., etc.

Data availability

No data was used for the research described in the article.