Possible Effects of Blockchain on Medical Markets PDF

Possible Effects of Blockchain Technology on Drugs Authenticity Management in the Medical Market Tzefania Aviv and Dr. Maoz Hanan Management Department...

Possible Effects of Blockchain Technology on Drugs Authenticity Management in the Medical Market Tzefania Aviv and Dr. Maoz Hanan Management Department Bar-Ilan University, Ramat-Gan, Israel Abstract Purpose: This article delves into the ability to increase the levels of authenticity control of drugs and medical products to cope with counterfeit and dangerous drugs. It aimed to support the global and documented public interest in this field by proposing to combine blockchain technologies and smart contracts in medical supply chains, to achieve multinational control on drugs authenticity. Methodology: The study developed a techno-logistics model based on SEM, which contains five key parameters for measuring the effectiveness of blockchain in medical supply chains, and for improving supervision and control abilities. Dataset was collected from professional and business experts through in-depth interviews and surveys and analyzed using SmartPLS software. Findings: The results shows that 60% of the possible improvement in the medical market ability to supervise medical products authenticity (significance level of 0.05) is explained by the proposed model. The model validated all included parameters and managerial interactions. It concludes that combining blockchain technology and smart contracts will present stricter and more reliable quality control levels in medical supply chains, thus enabling a new global medical security envelope for public health. Value: The article, led by three different disciplines, technological, logistical, and medical, harnesses a multi- dimensional model for maintaining public health in the medical markets. Research findings may serve as a foundation for developers, researchers, and professionals to initiate platforms buildings and products creation to advance the authenticity and quality of medical products distributed for public consumption. Keywords: Blockchain Technology (BCT); Smart Contracts, Supply Chain Management (SCM); Medical Market Effectiveness; Drugs Authentication Management. 1. introduction Blockchain technology is a database system that contain very low levels of active substances, and 30% records and distributes data on transactions, do not contain active substances at all and lack any controlled by agreement of the system participants medical value. and stakeholders, and is secured via cryptography The issue of frauds in the pharmaceutical sector, (Kosba et al., 2016). The technology is highly including counterfeit or substandard drugs, is a advanced in terms of creating management controls sensitive and significant one in the public health and authentic supervision of data, users, and space, requiring cautious and meticulous care that transactions in business and organizational processes may possibly save lives. It is significantly difficult to (Kim & Shin, 2019). identify whether an acquired drug is original and However, there is negligible literature on the reliable, a difficulty that turned into a global implementation of blockchain-based supply chains to complication which has been reviewed by leverage the managerial advantages among professional elements in UN committees (World stakeholders and boost the reliability of supply chains Health Organization [WHO], 2017). in medical markets. Business articles and global media outlets have The motivation for this paper stemmed from previous generated an unignorable media echo about the publications by WHO (World Health Organization, public health risk inherent in the counterfeit drugs 2017), which indicated that the industry volume of market. According to Colorcon (Rajabi-Siahboomi & the counterfeit drug supply chain is estimated at USD Pond, 2021), the volume of the counterfeit drug 200 bn., constituting approximately 2% of the total supply chain is estimated at USD 200 bn. - global sector. Such unauthentic drugs that reach approximately 2% of the total sector revenues, posing public shelves pose a real danger to patient health, a grave threat to patients. WHO (2017) estimated that and a significant one to the integrity and credibility of some 16% of all counterfeit drugs contain incorrect public service systems. According to WHO, some 16% drugs, whereas 17% contain incorrect levels of active of all counterfeit drugs contain incorrect drugs, 17% substances. Furthermore, over 30% of the counterfeit drugs discovered in the market do not contain any decentralized database based on open code, active substances and lack any medical value. accessible and available to the public, which is Counterfeit medical products and medical frauds in composed of blocks that contain transaction data, the chains of supply often include toxic compounds timestamp, and a link to the preceding block that may cause negative heath implications. (Pahlajani et al., 2019). The code is free to use, view According to a report by CNN (Susan, 2019), between and redistribute. Creating a new block of data is only 100,000 and 1,000,000 individuals die every year due enabled once the entire blockchain algorithm is to counterfeit drugs and, in countries with a relatively deciphered, requiring the consensus of all other low economic classification, drugs can be participants in the distributed network (users, fraudulently sold and account for up to 70% of all stakeholders) (Tavares et al., 2020), which is supply in a certain niche. achieved via Proof of Work (POW) (Alharby & Whereas brands and manufacturers attempt to Moorsel, 2017) or other similar methods. This integrate a package-level means of location and process prevents duplicate entities in data authentication security (Gupta et al., 2004), such step management (Tavares et al., 2020), disallows is not sufficiently effective to discover or block frauds changing, editing, or erasing data, and increases the taking place in the deeper links of the production and business confidence among all stakeholders, supply chains. Blockchain technology enables the efficiently and automatically (Hald & Kinra, 2019). establishment, management, and supervision of The core technology and innovation of blockchain records related to production and supply data relies on the blocks being encrypted through a alongside varied medical data, from initial raw combination of both private and public keys, a state- material handling to final supply to consumer, the of-the-art asymmetric encryption that constitutes a technology uses supplemental components, e.g., new benchmark for data authentication in Internet of Things (IoT), Artificial Intelligence (AI), stakeholder networks (Tavares et al., 2020). Another and Smart Contracts (Kim & Shin, 2019) to track, unique aspect is its decentralized management supervise, manage, verify, and ascertain that a drug or mechanisms that generate a system impervious to medical product meets all global development and fraud, resulting from the managed and centralized regulation criteria. control of a certain entity (Tavares et al., 2020). This This paper focuses on the technological-business technology was demonstrated with a use case value inherent in the implementation of blockchain scenario for the decentralized currency Bitcoin technology in the medical sector supply chains. The (Nakamoto, 2008), which is managed by an affiliate research objectives were: (1) examine the possible network and enables protected and authenticated effects of the unique components of blockchain business transactions, without the involvement of technology on the effectiveness and efficiency of external elements in its management (Nakamoto, supply chains in the medical markets; (2) propose a 2008). conceptual model to examine the nature of the Kim & Shin (2019) emphasize three properties of relations between investments in technology in blockchain technology, namely: transparency, medical supply chain efficiency; (3) examine the level decentralized management, and inability to change of authentication that can be provided to the data. substandard and counterfeit drugs market by The first property, transparency in the blockchain implementing technologies for management control; system (Kim & Shin, 2019) enables access for all users (4) reach conclusions regarding the novel to all data and accounts, including the full transaction contribution of blockchain technologies toward such history, with maximum transparency (Kim & Shin, endeavors; (5) propose new directions for research 2019). Data transparency occurs when all the toward development of an applied (technological, relevant information is visible, can be tracked by all logistical) model in the pharmaceutical industry. participants, and is updated automatically and Two main research questions were formulated to simultaneously for all actors participating in the model, collect, and analyze data: network or supply chain. The transparency improves RQ1. what are the unique components of the fairness perceived by all participants, obviates the blockchain technology that impact the need for middle-men, increases efficiency, and effectiveness of supply chains in the minimizes risks (Kouhizadeh & Sarkis, 2018). For medical market? production and supply chains, blockchain RQ2. what is the level of impact of blockchain- applications enable tracking of the origin and flow of based supply chains on implementing products, processes, and events; monitoring of the authentication processes of drugs and transacting parties; and documentation of the related medical products in the global health timestamp. The technology can be connected to industry? supplemental monitoring products, e.g., IoT, RFID, etc. (Gupta et al., 2004), which document the 2. Literature review electronic records, thereby instilling confidence in 2.1. Blockchain Technology control processes (Kouhizadeh & Sarkis, 2018). In the Blockchain technology was initially developed in consumer world, transparency is associated with 2008 by Satoshi Nakamoto (Nakamoto, 2008) as a consumer trust (Kim & Shin, 2019), removes information blockages in the form of middle-men and The organizational Resource Based View theory gatekeepers, and allows consumers to personally (RBV) (Barney, 1991) proposes, inter alia¸ a track all movements of the products they are managerial setting for determining the resources an acquiring and consuming (Azzi et al., 2019). organization can arrange and leverage to obtain an The second property, blockchain-based achievable and sustainable competitive advantage decentralized management, occurs when the (Maoz et al., 2007). Blockchain technology may database is not controlled by a certain single entity, support the processes of converting resources and but rather by affiliates (Hald & Kinra, 2019) in the capabilities into real competitive advantages. supply chain. Moreover, transitioning from a The Network Theory (NT) (Bower, 1981) examines centralized network to a decentralized network structures of business networks from a sociological reduces the possibility of fraud by a central entity perspective and deems the establishment of dyadic (Wright & De Filippi, 2015) and facilitates the (interaction between two individuals) relations as the establishment of a consensus upon approving elementary basis for generating business confidence transactions and authenticating data (Kouhizadeh & among the business companies and networks weaved Sarkis, 2018), thereby boosting the perceived level of by them (Treiblmaier, 2018). According to such transactional confidence. Furthermore, decentralized theory, the premise of business behavior among management enables equal commercial actions actors in the supply chain is based on the creation of among the actors, naturally forgoing issues of a strong web of trust among details and individuals, nationality, borders, limitations, and blockages that and the conversion of such web to inter- exist in the traditional, normal trading world (Wright organizational trust for the purpose of sharing & De Filippi, 2015). information and business development. A The third property (Kim & Shin, 2019) is blockchain-based supply chain expands the theory technological in nature, with extensive effects on into the digital age of the 21st century, proposing the management methodologies. The immutability data planning of reliable business communication, albeit in blockchain, the lack of system admin access for not one based on dyadic human trust, but rather on a editing, amending or changing historical data technological mechanism that is database-based, (Kouhizadeh & Sarkis, 2018), which is common in lean, smart, and decentralized, which generates a normal databases, significantly reduces the capability credible and authenticated environment for doing of manipulating the data and maintains strict and business, transparent to all dyadic actors, and unchangeable documentation of the accumulated unchangeable (Treiblmaier, 2018). Personal relations data history (Azzi et al., 2019). This property are not redundant; however, their overall essentiality solidifies fundamental and rooted trust among the might change as using blockchain does not require a managing actors, even in the lack of a reliable dyadic trust system in the supply chain, but rather a middleman. technological one (Werbach, 2018). The Principal Agent Theory (PAT) (Jensen & Theoretical background Meckling, 1976) presents a central challenge in a The Transaction Cost Theory (TCA) (Williamson, supply chain in which the chain manager selects the 1979) argues that organizations will favor developing agents that form the chain, develops relations based optimal business structures based on the desire to on trust, contracts, expectations, and business achieve economic efficiency. Such efficiency will be controls, over time and according to processes. The achieved by minimizing the costs of transacting with theory examines “how to design optimal contracts the market and constantly searching for quality between the actors, manager and agents, to avoid alternatives bearing reduced costs. The theory claims asymmetric information errors.” (Treiblmaier, 2018). that organizations will reach an optimal structure if As business spaces are characterized by asymmetric they minimize the costs of developing, executing, and flow of information (multiple external sources, monitoring transactions, thereby supplying a clients, vendors, partners, communication networks managerial basis for outsourcing or insourcing for each manager and agent in the chain), then decision-making in supply chains. The theory, in fact, optimal performance must be based on basic trust, defines the borders of organizations, their size, shared interests, and command & control systems, all governance systems, and investment allocation and of which are aimed at minimizing the asymmetric feasibility tests (Treiblmaier, 2018). When aiming the information gaps. The organizational effort invested theory’s lens at blockchain technology, seemingly in such performance control requires the there is real potential to achieve supply chain establishment of expensive mechanisms (Jensen & efficiency by reducing the development, execution, Meckling, 1976) to make the flow of information and monitoring costs of transactions in the chain, transparent and accessible to all actors. Blockchain’s improving organizational governance by redefining smart contract technology provides an elegant borders and arrangements with business partners, solution for the entire command & control system of and changing the method by which business the information that flows among actors creates a information is managed, with transparency and transparent, authenticated, and unchangeable credibility among all stakeholders (Treiblmaier, dataset, thereby minimizing the asymmetric 2018). information gaps (Treiblmaier, 2018). The automatic management of smart contracts grants all parties of are severely sensitive to authenticity control of the manager-agent system a real guarantee for medical products (Schöner et al., 2017), constituing a effective planning, meticulous execution, and major problem that worries the global industry. automatic supervision of the relations among the Existing solutions that propose information systems actors, manager, and agents (Korpela et al., 2017), with central command (ERP, SCM) that pose a threat thereby significantly alleviating the information to data integrity, availability, and felixibilty, are also asymmetry challenge. exposed to information fraud and managerial corruption (Azzi et al., 2019) as only a few 2.2. Smart Contracts administrators have access to the global data. Smart contracts developed as a blockchain-based On the other hand, the integration of advanced technology to create a digital, reliable, authenticated blockchain technology in supply chains provides a and unhackable system of contracts among technological and automatic platform for a strategic stakeholders in business networks. The smart and transparent partnership, one that is impermeable contract, its framework, and contents, are formulated to supply chain data changes (Kim & Shin, 2019) and and converted into computer code, then stored on the allows to overcome the problem of exposing central blockchain platform (Kouhizadeh & Sarkis, 2018). elements to editing and changing system data. A The smart contract includes management and blockchain-based supply chain enables digital command & control mechanisms over all agreement innovation and establishes new opportunities for details and ensures that the parties exhaust all of its increased chain efficiency (Hald & Kinra, 2019); terms, including manage contradictions, problems, provides unhackable control of process and product and exceptions in an automatic and equal manner, reliability (Kshetri, 2018); exercises supervision of one that is managed in a transparent and data and information credibility, including authenticated form (Kim & Shin, 2019; Kosba et al., authentication and supervision of changes 2016). A smart block-chain based digital contract (Kouhizadeh & Sarkis, 2018); implements a contains all the data required by the parties to monitoring system for the full lifecycle of a product’s transact and consummate all the terms, including origination and transportation along the supply chain financial management, regulation, and environmental (Kim & Shin, 2019; Pahlajani et al., 2019); and law (Alharby et al., 2018). Blockchain ensures that presents an essential solution for supply chain- contractual data remain permanent with no option of related challenges in the medicine and healthcare changing or updating once signed in the chain of industry. blocks (Tavares et al., 2020), thereby allowing 2.4. Supply Chain business trust automatic, known, and pre-agreed enforcement According to the conventional approach, the creation processes for all parties (Alharby & Moorsel, 2017). and management of a partnership within the supply The smart contract technology obviates the need for chain involves information sharing, shared active involvement and the frequent exercising of accumulation of resources, synchronization of human judgement in contract management, contrary decisions, and interest boosting (Kim & Shin, 2019). to the traditional contract in supply chains, in which This approach necessitates allocating significant trust among the parties, personal acquaintance and resources to managing, maintaining, and preserving multiyear experience, alongside active contracts the chain’s integrity vis-à-vis operating challenges, managed by reliable third parties (law offices), strategic changes, entry/exit of actors, procedures, constitute the management and authentication and both local and global legal regulation. system of transactions among stakeholders Furthermore, in supply chains in the pharmaceutical (Kouhizadeh & Sarkis, 2018). market, it has been found that the authenticity verification of the manufactured and transported 2.3. Supply Chain Management (SCM) products is inefficient (World Health Organization Efficiency [WHO], 2017). The possible transition to an Supply chains for goods and products have become unconventional, blockchain-based supply chain essential and complex in a vibrant global enables the pharmaceutical market to operate a novel environment, accelerating the multiplication of verification system to monitor the drug, its mediating information systems, actors, and production, packaging, and transportation, using regulators that manage the entire business barcodes, tags, sensors, and decentralized database communication between manufacturers and technologies (Schöner et al., 2017), thereby ensuring consumers (Azzi et al., 2019). Such complexity identification, managemenet, and primarily obfuscates the managerial transparency expected of verification of a drug’s production, from origin to its product origins, processing, storage conditions, and final destination (Schöner et al., 2017). Using shipping routes (Azzi et al., 2019). A central supply blockchain technology in the supply chain allows to chain challenge in numerous industries is the minimize the production and distribution of unsafe, possibility of implementing smart command & counterfeit, and incomplete products by improving control systems throughout the chain. The challenge processes for command & control of the product’s is prominent in the medicine and healthcare journey (Azzi et al., 2019), comosition, and materials. industries (Nayyar et al., 2019), as their supply chains Using the suitable sensors, it is also possible to for effective decision-making processes, to which all identify the environmental changes the product has stakeholders can agree in advance, thereby went through with time, e.g., light, heat, movement, improving the efficiency and reliability of supply humidity, pressure, etc. (Azzi et al., 2019). chains. This modern automation of verification and Proper flow of information in pharmaceutical supply command & control processes, provided by chain poses a significant challenge to the global blockchain, restores trust among stakeholders industry. Pharmaceutical chains are composed of relative to the authenticity of processes and product numerous supply sub-chains (raw materials, control. The blockchain system, in practice, obviates development, production, transport, etc.), and the traditional need of stakeholders to trust one managing them also requires transitioning through another, and thereby fundamentally reinforces the political and social gaps between countries (Yousefi & trust among system actors and obtains the level of Alibabaei, 2015). Additionally, pharmaceutical supply security desired by the participants (Kim & Shin, chains are characterized by enormous complexity 2019). For instance, retail groups and the world’s due to numerous regulatory standards. Wise use of leading food companies, e.g., Dole Food, Unilever, designated information systems can improve product Walmart, began working with IBM on using and supply quality in the pharmaceutical market, but blockchain technology to track the global food its implementation is unable to overcome production, transportation, and storage supply complexities, cultural obstacles, issues of chains. The motivation resulted from an outbreak at transparency and of trust, authentication, and Chipotle (Mexican grill company), which led to 55 command & control (Yousefi & Alibabaei, 2015). cases of severe infection (Kim & Shin, 2019). The blockchain-based IBM Food Trust platform (IBM, 2020) enables complete tracking of global food 2.6. Medical Market Efficiency supply chains, from manufacturer to consumer, based Proper flow of information in supply chains bears on smart contracts (digitally-signed documents significant potential for successful performance of managed in the blockchain that can verify the identity companies and organizations that operate in of all human and non-human elements involved pharmaceutical markets in the global industry, throughout the process (Kim & Shin, 2019), including dealing with the counterfeit drug epidemic. establishing a deep space of trust, one that is based on The challenge of constantly improving the business transparency, openness, and verification (Brooks, performance of pharmaceutical chains, which is 2015; Persona Global, 2018) among all actors. required to deal with the counterfeiting issue, occurs due to the existence of numerous supply sub-chains 2.5. Supply Chain industry compliance (raw materials, development, production, transport, Industry compliance, which is primarily determined etc.), the managing of which also requires by regulatory processes of countries or interstate transitioning through economic, social, and political organizations (e.g., United Nations) that regulate gaps between countries (Yousefi & Alibabaei, 2015). rules, regulations, and laws for supply chain conduct Additionally, pharmaceutical supply chains are (Nicole F. Church, 2014), can be digitally managed characterized by numerous regulatory standards using blockchain’s smart contracts. The contracts are (Yousefi & Alibabaei, 2015). It is clear that wise use of flexible and can contain any complex set of terms, designated information systems can improve product guidelines, restrictions, etc., and allow for the and supply quality in the pharmaceutical market, but variations between cooperating companies and its implementation is unable to overcome countries in a single supply chain (Nicole F. Church, complexities, cultural obstacles, issues of 2014). transparency and of trust, authentication, and The term compliance is expansive and normally command & control (Yousefi & Alibabaei, 2015), refers to the prior preparations, processes, and thereby lowering the performance of the controls conducted by organizations to meet the pharmaceutical market in dealing with the main issue system of laws, regulations, policies, service of eliminating counterfeit drugs and improving the agreements, and best or enforced practices in supply authentication of medical products. chains or service level agreements. Compliance The necessity of constantly improving the processes are generally managed under compliance pharmaceutical market’s performance in dealing with governance, which constitutes the strategic core of the counterfeiting and authentication challenges was policymaking and decision-making processes for reviewed in the study by Nayyar et al (2015). implementing the compliance policy. According to the researchers, the drug counterfeiting Blockchain-based supply chain enables epidemic poses a real threat to global patterns for comprehensive implementation of compliance fighting malaria, AIDS, tuberculosis, and others. In processes to all stakeholders in the supply chain, 2015, the scope of the epidemic was USD 75 bn exceeding any existing geographic, cultural, and legal (Nayyar et al., 2015) and rising, lacking any effective obstacles in complex chains. The system of smart mechanisms for controlling and mitigating the contracts enables complex sets of compliance rules phenomenon. The researchers identify three and to establish compliance governance that allows instances in which the market has troubles dealing with the counterfeiting issue on one hand, and the products offered to the public (Mwachofi & F. AI- required authentication processes on the other: 1) Assaf, 2011), the existing level of asymmetry in the underperforming market that is unable to deal with medical market (Mwachofi & F. Al-Assaf, 2011), and non-standard and deliberately counterfeit drugs; 2) wise consumer behavior in the medical market underperforming market that is unable to deal with (Mwachofi & F. AI-Assaf, 2011). According to the product fraud, unlisted drugs, or unlicensed products research premises and literature review, all of the that lack testing and approval processes; 3) indicators may be shaped and affected by the underperforming market that is unable to deal with existence and activation of blockchain technology, production errors or erroneous storage of products improving the medical market’s efficiency. that are then delivered to the market for sale, instead of being destroyed. In all three cases, the existing 3. Research model and hypotheses control systems of supply chains in the medical 3.1. Conceptual model development market have difficulties to successfully deal with the The developed theoretical model was used as a Figure 1 Conceptual Model required authentication processes to mitigate the framework for outlining the research lines of thought phenomenon. toward creating a multi-variable model (Elangovan, R This paper presumes that blockchain technology Rajendran, 2015) and formulate the main elements facilitates a more efficient market structure, i.e., composing the reciprocity between variables allows certain components of the current market (Eriksson, 2003), including a Cause Effect chart (Earp structure to behave according to economic and social & Ennett, 1991). The model relies on the main benchmarks that minimize costs, reduce theories reviewed in the paper, served as the basis for asymmetrical information, support increased analyzing a set of concepts, constructs, and indicators competition among numerous actors (actor (Elangovan, R Rajendran, 2015), and laid down competition), and focus on maintaining product foundations for formulating a set of hypotheses that homogeneity (product competition) (Mwachofi & F. became observational models (Elangovan, R AI-Assaf, 2011). Blockchain technology provides data Rajendran, 2015). arrays with transparency and symmetry for the The theoretical model was drawn as a value chain sharing of production and commercial information that uses blockchain technology (Kim & Shin, 2019), among stakeholders. The accumulated information is beginning with technology components, through unchangeable and monitored by all actors in any state supply chain efficiency (Cao & Zhang, 2011), to and at any time, focuses the competition on product factors that describe the pharmaceutical quality (homogeneity) since all trading components market’s performance (Mwachofi & F. AI-Assaf, and actors are known to everyone, enables numerous 2011). The conceptual model is described in Figure 1. actors, facilitates increased supply, and expands the The rational of the theoretical model is based on the tradability of medical products and services (Kim & implementation of blockchain technology, including Shin, 2019). In this form, blockchain technology can its sub-technologies, e.g.: databases, decentralized utilize tech and processes that support market forces network, encryption algorithms, smart contracts, (supply and demand); set qualities, prices, and digital currencies, etc. in supply chains for medical quantities; and optimize the medical market’s products and services. capability of dealing with counterfeiting issues and Such implementation shapes the business aspects of authentication challenges, all of which are exceptions the supply chain differently than other technologies of an effective system. have done in the past, including generating built-in The main components found to be suitable indicators business trust among all the chain partners, better of improvement in the medical market’s performance compliance with local and global regulation, and its efficiency in dealing with the issue of improvements in logistical efficiency, financial counterfeit drugs and authentication challenges are: effectiveness, command and governance, etc. The quality of medical services in the medical market theoretical model describes the final effect on the (Korpela et al., 2017); unhackable digital signing pharmaceutical market’s performance, primarily the features for all medical products (Gupta et al., 2004; improving of supervision and regulation processes Yao et al., 2010); market ability to generate healthy relative to trade protection; maintaining public competition among actors in terms of the quality of interests to reduce the trading volume of counterfeit manage within it. drugs; and constantly striving to protect public Based on the aforementioned, the research health. formulates the following hypothesis: H1 The main features of blockchain 3.2. Structural Model Development technology, including transparency, immutability, and The main latent variables were extracted from the decentralization, allow the establishment of better theoretical model to construct the structural model authenticity system that has value in a more reliable that contains the system of relationships between and efficient supply chain management. variables and the related set of hypotheses. Later, the research measurement model that collected 3.2.2. Smart Contract Based Blockchain empirical data on the studied phenomenon will be The smart contract is defined as a “digital transaction presented. protocol that executes the terms of the contractual transaction” (Kim & Shin, 2019) and allows to store 3.2.1. Main Features of Blockchain Technology agreements, share expectations, and independently A blockchain-based supply chain of products enables enforce legal components using blockchain. Each better access and transparency for all stakeholders in contract has a unique address that allows the supply the supply chain. This technology manages a perfect chain participants to manage the system of copy of the transaction log of all stakeholders in the expectations and agreements among the partners, chain, contains the full transaction history, and leads thereby increasing the level of mutual trust in the to complete disclosure and accessibility. Even if stakeholders’ ability to properly manage the supply external attempts are made to damage data integrity, chain (Kim & Shin, 2019) and optimize it via sharing such attempts can be rapidly exposed and discovered data, information, reservations, expansions, or (Kim & Shin, 2019). In this form, transparency is used innovations of activities. The enforcement as a deterrent against malicious attacks on the data mechanism hardcoded into smart contracts allows to network (Shin & Park, 2019). The fact that blockchain monitor, verify, and activate pre-agreed mechanisms is a database that unilaterally stores information and for payments and fines among all stakeholders is impervious to changes, edits, or deletion, improves (Saveen A. Abeyratne, 2016). Eventually, blockchain- the perceived reliability of marketing and financial based smart contracts enable cost reductions in statements in transactions among the supply chain’s managing supply chain data, brokering services, and partners (Kouhizadeh & Sarkis, 2018). in the need for outsourced legal and accounting Moreover, blockchain is naturally adapted to being services (Kim & Shin, 2019). programmed for processes and controls, and is Based on the aforementioned, the research therefore suitable for receiving compliance rules for formulates the following hypotheses: a system of laws, regulations, policies, best practices, H2a The smart contract has a positive effect and agreements between the supply chain partners on business trust among stakeholders in supply chain (Nicole F. Church, 2014), thereby improving the management. business trust between the partners as an essential H2b The smart contract has a positive effect element of the chain’s success. Eventually, the on the economic efficiency of supply chain decentralization of blockchain (each end station is management. also a server, and no central server exists, unlike 3.2.3. Supply Chain Business Trust Client-Server architecture) allows the supply chain to Supply Chain Business Trust refers to all the generate value with the participation and supervision information items managed within it, and mainly: (a) of all the supply chain participants (Hald & Kinra, reliability, transparency, and monitorability of 2019); increase the sharing of business processes via business transactions; and (b) reliability of votes or authentications by the majority of information on products or services managed in the participants (Kouhizadeh & Sarkis, 2018). In this supply chain. Blockchain-based supply chain manner, blockchain reinforces shared supervision of management reinforces business trust and the supply chain management (Hald & Kinra, 2019) and reliability of information on managed products (Kim establishes a consensus in terms of compliance with & Shin, 2019), primarily due to the inability to change regulation, laws, and standards (Nicole F. Church, data; network transparency for all members; 2014). management sharing; prior management of These features of blockchain technology enable the expectations via smart contracts; and the superior establishment of a system of smart contracts, i.e., security levels of data encryption and storage. Even algorithmics-rich software code that allows to the concern of human errors, inter-system structure the full wisdom of the supply chain among integration faults, and faulty passage of data between the stakeholders as a weave of blockchain software different content spaces, is automatically monitored contracts that contain all agreements, using blockchain and reduces human and system understandings, expectations, and behavior codes, all errors (Korpela et al., 2017). hardcoded by stakeholders in the supply chain of The technological capability of designing the supply which they are members, for the businesses that they chain in such manner that maintains the managed  Figure 2 The Structural Model business trust, alongside the reliability of information that is essential to industry and government on managed products, may boost the perceived trust compliance processes (Yousefi & Alibabaei, 2015). in the authenticity of the products and services Use of the smart contract sub-technology within managed in medical market supply chains, as well as blockchain allows to define a set of activation laws for the ability to optimize the pharmaceutical and product processes, development, and marketing, medical product markets. Simultaneously, use of thereby enabling automatic and documented input, advanced technologies, e.g., RFID (Yao et al., 2010) management, and supervision of compliance with and unique digital signatures (Gupta et al., 2004) standards, implementation of regulations, and ethics increase product authenticity and allow for supervision. Smart contracts are capable of comprehensive tracking of the supply chain process increasing organizational compliance with industrial and its cycle through the links. In practice, the best- and governmental requirements and reinforce the case scenario is being able to meet client needs while efficiency and reliability of medical supply chains also meeting the company’s business needs (Brooks, (Kim & Shin, 2019). 2015). The effective cooperation of users of formal Based on the aforementioned, the research systems significantly reduces the time and costs formulates the following hypothesis: involved in the communication process between the H4 Improvement of industrial and trade partners and is even predicted to improve the governmental compliance, in a blockchain-based probability of cooperative decision-making (Kim & medical supply chain, leads to increased performance Shin, 2019). Cooperation leads to cooperative efficiency in the pharmaceutical market. advantage, which leads to improved performance overall (Cao & Zhang, 2011). Figure 2 presents the structural model used. Based on the aforementioned, the research formulates the following hypothesis: 4. Research methodology H3 Increasing business trust in supply chain 4.1. Partial Least Squares (PLS) Method management leads to increased performance efficiency The research method used was PLS-SEM (Partial in the pharmaceutical market. Least Squares Structural Equation Modeling), which belongs to a family of statistical models that strive to explain relations in a system of latent and measured 3.2.4. Supply chain industry Compliance variables (Baron & Kenny, 1986). The PLS-SEM is Industry compliance is defined as a system of laws, composed of two sub-models: structural model and regulations, policies, best practices, service level measuring model. The structural model represents agreements, protocols, methodologies, and the relationship between the latent variables, and technologies established by the corporation to breaks down into the measurement model that perform, manage, and supervise compliance (Nicole represents the relationships between observable F. Church, 2014). Proper use of advanced information indicators (data) and latent variables. systems in supply chains enables increased According to Andreev et al. (2009), SEM is a considerably complex statistical technique (Gefen et organizational governance and compliance with al., 2000) for assessing relations between constructs, industry standards, as the systems are based on data including latent variables (LVs) and observed management, documentation, decision-making, and variables. LVs represent conceptual terms used to official reporting processes. Information systems may express theoretical concepts or phenomena. provide a level of transparency and process control Observed variables, also referred to as measures,  Figure 3 The measurement Model indicators, or items, are variables that are measured indicators are replaceable and removable in the directly. The research uses the SEM component- measuring and analysis process, as each of them based or Partial Least Squares (PLS), named as PLS- represents the construct qualities (Janadari et al., SEM. PLS-SEM is a distribution-free approach that 2018). Alternatively, a formative measuring model might be presented as a two-step method (Tenenhaus was tested and rejected, in which the linking arrows et al., 2008). The first step refers to path estimates of exit the indicators toward the constructs, thereby the outer (measurement) model used to compute LV expressing the unique and differing contribution of scores. The second one refers to path estimates of each indicator to building the construct’s set of inner (structural) model, where Ordinary Least qualities. This model is less flexible, as each indicator Squares (OLS) regressions are carried out on the LV removal may cause the construct’s meaning to change scores for estimating the structural equations. Unlike (Janadari et al., 2018). The decision of whether to covariance-based SEM (CovSEM), PLS-SEM attempts draft the PLS-SEM model as formative or reflective is to estimate all model parameters in such a way that not always a clear one (Andreev et al., 2009). the result should be a minimized residual variance of Numerous researchers rely on the definition and all depended on variables (DV), LVs, and observed commonplace reference to the research boundaries variables (of the reflective LVs) (Chin, 1998b; set in the indicators and constructs, and on prior Diamantopoulos & Siguaw, 2006; Gefen et al., 2000) premises, to define the relations between them. The namely, maximize the explained variance. In other SmartPLS system (Ringle et al., 2015) enables a words, the main objective of the PLS-SEM approach is solution to this problem by using a technique called to best predict of LVs by the DVs, instead of obtaining Confirmatory Tetrad Analysis (CTA-PLS), developed a good fit to the data, i.e., the main goal of the other by Gudergan et al., (2008). CovSEM approach. Thus, PLS is intended mainly for Assessment of confirmatory tetrad analysis (CTA- prediction purposes while CovSEM is focused on PLS) for measurement models was operated as it is parameter estimation (Andreev et al., 2009). consistent with partial least squares (PLS) path Consequently, PLS-SEM and CovSEM techniques modeling assumptions. It employs a bootstrapping differ in terms of objectives, assumptions, parameter procedure to examine vanishing tetrads in CTA-PLS estimates, latent-variable scores, implications, and allows in this research to distinguish between epistemic relationship between the latent variable formative and reflective indicators' specification. The and its measures, model complexity, and sample size results of the confirmatory tetrad analysis (CTA) in (Chin & Newsted, 1999). this research showed that for each construct all the The research’s measuring model was examined and values in the low adjusted confidence interval (CI) found to be reflective, in which the linking arrows exit were negative (-), while in the up adjusted CI were the constructs toward the indicators, thereby positive (+), meaning that zero lays between these expressing the construct’s set of qualities that is values, suggesting that the model was reflective. CTA- reflected in each indicator. Furthermore, the PLS is limited to check variables with 4 indicators and more. This research meets this requirement and most variables; protecting respondent anonymity; of them got more than 4 indicators for latent variable. reducing concerns of evaluation; and improving the Finally, collected data was checked for missing scale. In the second part, after collecting the data, values. As there were less than 4% of values missing statistical control was performed using a preliminary per indicator, missing values were treated with mean test of the data bias level, which tests the Variance value replacement. A bootstrapping technique was Inflation Factor (FIV) values; values lower than 3.3 used to generate parameter coefficient estimates and are desired. The results indicated that all VIF data t-values with 5000 subsamples from the original were under 3.3 and that the model is free of Common dataset and no sign changes, including mediating effecting analysis as per (J. F. J. Hair et al., 2013; Method Bias (CMB) (Kock, 2015). Preacher & Hayes, 2008; Sattler et al., 2010) 4.4. Data analysis 4.2. Measurement model development Measurement model analysis was conducted The measurement model was derived from a according to PLS-SEM (Akter et al., 2016), which has development of the conceptual research model seen extensive use in social sciences research in light (Elangovan, R Rajendran, 2015) and contains latent of its suitability for empirical analysis of sample sizes variables in its three content spaces. In content space smaller than 200 observations, and even data with A, called Blockchain Technology, two constructs were unusual data distribution (Joe F. Hair et al., 2014). developed: Main Blockchain Features (MBF) and Additionally, PLS-SEM handles a probing research Smart Contract Based Blockchain (SCBB); in content structure that proposes structures and models with space B, called Supply Management Efficiency, two new constructs that have not been empirically constructs were developed: Supply Chain Business validated yet (Joe F. Hair et al., 2014; Yadlapalli et al., Trust (SCBT) and Industry Compliance (IndComp); in 2018). The method is very common when researching content space C, called Medical Market Performance, supply chain performance (Han et al., 2017; Jeble et one construct was developed: Medical Services al., 2018), and at any rate serves as an excellent Efficiency (MSEf). The development of the constructs database for analyzing the research questions on and their content aspects was conducted based on the market management, supply chain management, and extensive literature review that is detailed in this technology management. Respondents' paper. See table in the Appendix A. demographics include operation-oriented and services-oriented jobs (63%, 28%), with juniors (1- 4.3. Sampling design and data collection 5), professionals (6-15) and expert (15+) experience Data collection included two main stages: pilot and (59%, 17%, 23%), bachelor’s degree and graduated complete survey. The pilot stage was designated to (62%, 38%), when 80% of them are from the examine the survey content and proposes processes engineering study field. for improving accessibility and preliminary content and structure validations and was sent to four 5. Findings blockchain researchers and professionals for Since the research adopted the PLS specific two-stage feedback and was corrected accordingly. The pilot assessment procedures (Chin 1998; Hair et al. 2013; results improved the content’s validity and clarity. Hair, Ringle, and Sarstedt 2011; Hair et al. 2012; The complete survey stage used convenience Reinartz, Haenlein, and Henseler 2009), it conducts, sampling, which is considered a practical solution for in the first stage, a construct-level of analysis to assess collecting reliable data and was compatible with this the measurement model, followed by a second stage research, and was distributed to 107 professionals in of structural model assessment. This study utilized the engineering, economics, and management the SmartPLS 3.3 software and followed Ken Wong's industries who hold operative and service-related (Wong, 2013a) book on PLS-SEM. positions. As a result, 81 surveys were collected, all of which were found to be validated for empirical 5.1. Measurement Model Assessment processing. Model Estimation and Convergence As the survey was structured for response by a single To assess whether our measurement model respondent, the Common Bias Method (CMB) that specification is sufficiently good to converge into occurs when variations in responses are caused by results, we analyzed the number of iterations that the Smart-PLS Algorithm has reached while the measurement tool (survey), was solved in two converging the research data into results. According parts: first, prior to the survey, the measurement tool to Ken Wong's (2013b), an expected figure of under is treated using preliminary procedural control 300 iterations will support the notion of having a components in the planning and distribution of the model with sufficient sample size, non-existence of survey; and second, after collecting the data, the tool outliers, and adequate indicators without many was calibrated using statistical control of all identical data. respondents and responses (Conway & Lance, 2010; Podsakoff et al., 2003). In the first part (survey planning and distribution), use was made of procedural remedies, including establishing a close separation between the dependent and independent Test results of the converging algorithm were Blockchain Features construct was found to be 0.595, finalized after 7 iterations, so it can be concluded that while the threshold sis 0.6. As, on one side, we refer this research’s measurement model is stable and to this research as an exploratory one, on the other, appropriate. the Cronbach’s alpha and composite reliability test results satisfy the desired thresholds; we accept that Figure 4 Measurement Model; Original Output from SmartPLS Indicator’s Reliability these results have internal consistency. Indicator reliability is the proportion of measure variance that is explained by the latent variable. Outer Convergent Validity loadings are observed to determine indicator Convergent validity is used to identify the extent of reliability. Values of 0.7 or higher are preferred, while which a measure correlates positively with 0.4 or higher are acceptable for exploratory research alternative measures of the same construct. Average (Hulland, 1999). The research reliability tests were variance extracted (AVE) measures convergent conducted as described below. The results indicate validity on the construct level with the criteria of 0.50 that all values are higher than 0.581, i.e., an or higher. AVE values prove the sufficient presence of acceptable value for exploratory research. convergent validity. Internal consistency Discriminant validity Internal consistency reflects the extent to which Discriminant validity is the degree to which two measures within an instrument measure vary conceptually similar concepts (in this paper there are according to the same characteristic or construct. four exogenous constructs of main blockchain Internal consistency in social science research is features). Discriminant validity was assessed using traditionally assessed using Cronbach’s alpha, which the Fornell - Larcker Criterion and HTMT tests. First, tends to provide a conservative measurement in PLS- as recommended by Fornell & Larcker, (1981) , the SEM. Prior literature has suggested the use of square root of the AVE for each construct should be Composite Reliability as a substitute (Bagozzi & Yi, greater than its highest correlation with any other 1988; Joseph F. Hair et al., 2012). For both tests, the construct. As indicated the square roots of all AVE desired thresholds are 0.6, which are acceptable in values satisfy this criterion. Second, we looked at the exploratory research, and exclude main blockchain cross loading (Appendix B), which states that each features for the purposes of Cronbach’s alpha. construct shares larger variance with its own A contemporary view of PLS suggests that instead of measures than with other measures. Thus, an using Cronbach’s alpha and composite reliability, one indicator's outer loadings should be higher than all of should consider using the rho_A coefficient to check its cross loadings with other constructs. The appendix the reliability of PLS construct scores (Theo K. indicates that the model used in this paper meets the Dijkstra & Henseler, 2015). Generally speaking, a cross-loading requirements and supports the notion “rho_A” value of 0.7 or higher is preferred to that discriminant validity exists among the demonstrate composite reliability, while a value exogenous constructs. exceeding 1 is abnormal and should not occur in the Although the Fornell-Larcker criterion is a frequently model. applied approach for assessing discriminant validity, The test results indicate satisfying values for rho_A when used in combination with results of variance- and Composite Reliability for exploratory research. based structural equation modeling, such as An exceptional Cronbach’s alpha value for the Main traditional partial least squares path modeling and generalized structured component analysis, the research case, between four exogenous constructs. Fornell-Larcker criterion lacks sensitivity (Rönkkö & Social sciences guidelines for assessing f2 require that Evermann, 2013). values of 0.02, 0.15, and 0.35, respectively, will A novel approach for assessing discriminant validity represent small, medium, and large effects between was introduced by Henseler, Ringle and Sarstedt constructs (Cohen, 1988). The research results (2015): the Heterotrait-Monotrait Ratio of indicate a small effect of main blockchain features to Correlations (HTMT). The HTMT is a measure of smart contract-based blockchain, moderate effect of similarity between latent variables. If HTMT < 1.0, smart contract-based blockchain to industry then discriminant validity can be regarded as compliance, industry compliance to medical services achieved. As shown in Table 4, this paper’s results are efficiency, and large effect of smart contract-based beyond acceptable. blockchain to supply chain business trust, industry compliance to medical services efficiency, which 5.2. Structural Model Assessment support the differentiation between four exogenous Following the tests on the measurement model, the constructs. structural model was assessed. The results presents the explained variance (R2) and Predictive Relevance Q2 the standardized path coefficient, attached with level Stone-Geisser’s Q2 value (Geisser, 1974; Stone, 1974) of significance using bootstrapping technique. is a measure of the model’s out-of-sample predictive The results of the main PLS performance tests power or predictive relevance. In the structural support the hypothesis that: H1 (β=0.376, p