A Conceptual Model for Managing Pharmaceutical Supply Chain Risks through Technological Innovations

Purpose This study aims to comprehensively map and prioritize risks in the pharmaceutical supply chain, focusing on European and North American countries through a multi-actor perspective. Design/methodology/approach Through a structured literature review on supply chain risk management in the pharmaceutical supply chain, we identified 84 risks. After shortlisting the 15 most critical ones, we applied the analytic hierarchy process to prioritize risks affecting the pharmaceutical supply chain, considering both the perspective of individual actors and the entire supply chain. Findings This study first analyzed the pharmaceutical supply chain risk management literature to identify the most critical risks. It then offered a novel perspective on risk prioritization through a multi-actor analytic hierarchy process, revealing how different actors assign varying levels of priority to these risks based on their unique roles and business contexts. Originality/value Recent disruptions, such as COVID-19 and the Ukraine conflict, reshaped pharmaceutical supply chain risk priorities, revealing a ranking that diverges significantly from the literature. Each supply chain actor prioritized risks differently based on their role, highlighting a fragmented approach and emphasizing the need for more collaborative, systemic risk management. This study introduces new research directions to address unmet, real-world needs within pharmaceutical supply chain risk management.

Implementation and adoption of new technologies are gaining the result of smooth supply chain and logistics operations. Internet of things (IoT) artificial intelligence, including data mining, intensified in all fields of life, particularly in supply chain management and operations. Blockchain technology has the capability to reform the supply chain and logistics operations management. Blockchain provides digital database solutions for all transactions across supply chain and operations management. Radio frequency identification device (RFID) is also helping technology transmit electromagnetic waves to radio-compatible integrated circuits to look after and manage the entire supply chain and logistics operations management. The Fourth Industry Revolution 4.0 refers to the automation, interconnectivity, machine learning, and real-time data that help supply chain and logistics operations management in the 21st century.

The increasing complexity of healthcare supply chains characterized by fluctuating demand, stringent regulatory requirements, globalized procurement networks, and the critical need for real-time resource availability has accelerated the adoption of Artificial Intelligence (AI) as a transformative operational tool. This systematic review synthesizes emerging trends, empirical findings, and technological innovations in AI-enabled supply chain management within healthcare systems. Drawing on peer-reviewed literature from the past decade, the study examines how AI-driven techniques such as machine learning, predictive analytics, natural language processing, optimization algorithms, and intelligent automation enhance procurement forecasting, inventory management, logistics optimization, clinical resource allocation, and risk mitigation. The review highlights the growing integration of AI with enabling technologies such as digital twins, Internet of Medical Things (IoMT), blockchain, and cloud-based analytics to strengthen supply chain visibility, traceability, and resilience. Evidence shows that AI significantly reduces stock-outs, improves demand prediction accuracy, enhances cold-chain monitoring, and supports decision-making in critical service lines such as pharmaceuticals, surgical supplies, and emergency care. Despite these advancements, major challenges remain, including data fragmentation, interoperability limitations, model transparency concerns, workforce capacity gaps, and ethical issues relating to bias, privacy, and automation risks. The review concludes by outlining future research directions, emphasizing the need for explainable AI (XAI), scalable real-time analytics, integrated data governance frameworks, and hybrid human-AI decision architectures. This study provides a consolidated knowledge base for policymakers, healthcare administrators, and supply chain professionals seeking evidence-based pathways for AI adoption in healthcare operations.

The effective management of pharmaceuticals in the National Health Service (NHS) is critical to patient welfare thus any risks attached to this must be identified and controlled. At a very basic level, risks in the pharmaceutical supply chain are associated with product discontinuity, product shortages, poor performance, patient safety/dispensing errors, and technological errors (causing stock shortages in pharmacies) to name but a few, all of which incur risk through disruption to the system. Current indications suggest that the pharmaceutical industry and NHS practitioners alike have their concerns as to the use of generic supply chain strategies in association with what is perceived to be a specialist product (pharmaceuticals). The aim of the study undertaken was to gain a more realistic understanding of the nature and prevalence of risk in the Pharmaceutical Supply Chain (PSC) to be used as a basis for a more rigorous research project incorporating in-vestigation in the UK, Europe and USA. Data was collected via a workshop forum held in November 2005. The outputs of the workshop indicated that there were thirty-five prevalent risks. The risks were rated using risk assessment catego-ries such as impact, occurrence and controllability. The findings indicated that the risks identified are similar to those prevalent in industrial supply chains, regardless of the idiosyncrasies of pharmaceuticals. However, the group consen-sus was that caution must be applied in how such risks are addressed, as there are aspects of the product that highlight its uniqueness e.g. criticality.

Nowadays business world requires more collaboration along supply chains in order to sustain production, optimize cost structure and speed up delivery. The growing inter twist among supply chainpartners causesnumerous risks whose impacting magnitude and scope are larger than ever before. The risks are not just limited in operations any more but further extend to relationships related aspects. It demonstrates new features that we think should deserve careful investigation. Although supply chain risks and partnerships are great concerns in both academics and industry, the existing literature seldom links them together, and it echoesinadequately upon the new situations happened in the past decade. As such, this research project is made with ambition to improve the understanding of risks in the context of today’s collaborative supply chains where interorganizational linkages are strengthened through partnerships.
\nThe research project contains three studies. They constitute an integrated series subjected to the overall research objective. The first study starts with concept building and fundamental notion rethinking of risks in supply chains. We conceptualize supply chain risks into a general form in which risks are integrated into a system capable to reflect the correlation and chain effect among them. Through analytical inference and simulation it is found that the level of collaboration of partners contributes to the resilience of supply chains. It implies that partnerships can positively affect the integration of supply chain risk system, thus enhancing supply chain operations by improved ability in fault recovery.In the following two studies we are concerned with the impacts of different types of risks in supply chains upon companies’ operational performance given the effect of partnerships. The pre risk event effect and post risk event effect of partnerships are investigated in study two and study three respectively. The second study uses survey to research practitioners’ view on the role of supply chain risks and partnerships in supply chain performance. The validated sample of 162 responses reveals that the depth of partnerships imposes the most significant impact on supply chain risks and the collaboration risks are considered the top risk type that can influence supply chain performance to the most extent. The third study focuses on the negative consequence brought to the companies by supply chain risks when they have been realized. Event study is employed as the research methodology to identify and analyzethe effects of different risks under different partnerships. With respect to impact analysis, relationship risks are shown to cause the most significant loss to firm value. Moreover, deeper partnerships are found to have more negative impact on firm value resulted from relationship risks.
\nThis research project could contribute to the supply chain risk management literature by furthering the understanding of the important role of supply chain risks in enhancing the company’svalue and operational performance. The findings uncover the crucialrelationship between partnerships and supply chain risks, offering a novel view from a risk perspective to explain why an increasing number of supply chain companies are consciously engaged in partnerships nowadays. They may confer academicians and industrial practitioners with some new insights for risk management in supply chains and encouragefuture research in this area.

Supply chain management is a discipline dealing with organization, coordination, and optimization of relations within supply chains. Complexity and dynamics of supply chains are not always proportional to their reliability, and supply chain risk management becomes a very important tool in minimizing risk and uncertainties caused by, or impacting on, logistics-related activities or resources in the supply chain. Because risk modeling presents a very important segment of risk management, the paper includes a description of the main characteristics of supply chains and a model for risk assessment based on the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) methods. The main intention of the research presented here is to propose approaches based on application of the AHP and FAHP methods which are used as a tool for ranking supply chain risk categories, determining its share in total risk, and as a method for the supply chain risk assessment. The proposed approach is based on the experience and the knowledge of experts from insurance companies which are professionally engaged in the process of risk assessment, and possibility of its application is tested on a numerical example.

The beef and red meat sector in Australia is undergoing rapid change because of globalization, a highly competitive beef and red meat market (local and export). Risk management in the Australian beef and red meat supply chain has become increasingly important as companies both large and small seek to extend their global reach. It is important to manage these supply chain risks. The purpose of the conceptual paper is to present a framework for managing supply chain risk in the Australian beef and red meat industry. The supply chain risk management strategy is critical and significant to strategically support the supply chain and business success in the long run. However, little research has been conducted in the industry so far. Based on the resource-based view (RBV) approach, the firms’ capability is considered as effective tools for mitigating the supply chain risk in the real operational environment. The paper identified major types of supply chain risks in the red meat industry. The conceptual framework focuses on the relationships among the firms’ capabilities and supply chain risks. This provides insights into the supply chain risk management. Although, the study focuses on the Australian red meat industry, the proposed framework can be validated with an empirical work in different sectors. Moreover, this paper contributes to the supply chain risk management literature.

Supply chain is one of the most important parts for the company and supply chain management plays an increasingly important role in business development. Supply chain risk has become a major obstacle to supply chain management, and it makes a deep influence on company`s operation and development. The intricacies of the supply chain network structure, the external environment of uncertainty and supply chain managers excessive pursuit of lean, making the supply chain is vulnerability and the supply chain is increasingly vulnerable to various risks impact. Lean supply chain system which more and more companies used can provide the potential benefits, but with the pursuing the ability to respond faster and at lower cost, this system is becoming more and more fragile, and the impact of risks and uncertainties should be more sensitive. Globalization let supply chain have become more uncertainties. The company`s procurement and logistics part have covered different countries or area, which lead to the supply chain risk higher than before. This paper analyses the background and definition of supply chain risk in procurement and logistics. And collect and analyse the risk management method to assess, evaluate, identify, and manage supply chain risk.

The pharmaceutical business in Nigeria is not an exception to the rule that government rules and regulations are essential to preserving efficiency and order in a variety of industries. This study investigates the effects of laws and rules on the pharmaceutical industry's supply chain. Using a survey methodology, the study first took into account 1,881 people in total, but the Raosoft sample size calculator helped them reduce that number to 320. Participants were given a structured questionnaire to complete as the main method of gathering data, and linear regression analysis was used to examine the results. The results showed that government regulations had a major effect on supply chain management effectiveness. It was observed that while technological integration might improve supply chain operations, difficulties enforcing rules can impair supply chain performance. These revelations clarified the connection between supply chain performance and regulatory frameworks in Nigeria's pharmaceutical sector. To facilitate smooth implementation of policies, it is essential to include relevant stakeholders from the pharmaceutical sector in the policy development process. Therefore, it is recommended that effective administrative structures and consistent policies be established to promote growth and development. Additionally, involving stakeholders in the supply chain process and integrating technology are critical for achieving effective supply chain performance.

In many sectors such as supply chain, manufacturing, regular farms, health care, and pharmaceutical industries, traceability at real time and item level is important. This paper inquires the challenges of supply chain holders in the farming sector and proposes solutions using IoT (Internet of Things) for automatic tracking particularly for supporting functions like demand planning, inventory management, transportation in supply chain management. We introduce a framework of centralized traceability system based on IoT connecting all the elements providing end-to-end solutions thereby minimizing the overall loss. IoT security is of urgent concern because of the growing number of IoT products, the complexity of protocols used in IoT, and the manufacturers’ limited safety measures embedded in the devices. New vulnerabilities such as man-in-the-middle attacks, denial of service attacks occur due to unsecured channels of communication. We extend the proposed framework by adopting a security model to prevent man-in-the-middle attacks in an IoT environment. Furthermore, temperature and humidity values are tracked and analyzed using sensors at different timestamps.KeywordsInternet of things (IoT)TraceabilitySecurityFarms

This research investigates the strategic management of pharmaceutical supply chains in South Africa, with a focus on responses to disruptions resulting from the COVID-19 pandemic. The study explores how supply chain professionals navigated unprecedented challenges and implemented resilience strategies during this crisis. A qualitative, exploratory phenomenological approach was employed using semi-structured interviews with 25 pharmaceutical supply chain professionals selected through purposive sampling. Participants represented diverse segments of the pharmaceutical supply chain, including manufacturers, distributors, wholesalers, and retailers. Data were analysed using thematic analysis with Atlas.ti software to identify patterns and relationships within participant experiences. Four major themes emerged from the analysis: (1) disruptions in supply chains due to COVID-19, characterised by panic buying, logistical challenges, and inconsistent supply; (2) impact on strategic decision-making and operational performance, including implementation of skeleton staffing and increased operational costs; (3) resilience and responsiveness strategies, focusing on supplier relationships, enhanced demand forecasting, and increased local production; and (4) lessons learned and future preparedness, emphasising disaster management frameworks and technological advancements. The study highlights the importance of developing balanced strategic approaches that address immediate disruptions and long-term resilience in pharmaceutical supply chains. Key findings reveal that effective strategic management during crises requires simultaneous attention to operational adjustments (skeleton staffing, remote work) and strategic initiatives (local production, technological investment). These insights contribute to understanding how pharmaceutical supply chains in developing economies can enhance resilience against future disruptions through strategic management practices that balance reactive and proactive approaches.

Pharmaceutical supply chains experience delays and disruptions affecting access to essential medicines across regions. These challenges are caused by weak forecasting, long procurement cycles, fragmented distribution, poor quality data and shortage of skilled workers. These factors are managed with both forward looking and response-based approaches. Regular stock review, good communication, fast purchasing and close supervision help limit shortages. Response-based strategies like keeping extra stock may instead prove unsustainable over time. Supply chain structure can be adapted to product risk and working with suppliers can improve the ability to manage uncertainty. Flexible systems, real time information and robust internal processes allow quick responses and prevent major supply failures. Similar risks are faced by pharmaceutical firms worldwide when setting up supply networks. Other common problems are product faults, sudden halts in production, slow order handling, late shipments and poor matching of supply and demand. Rather than taking these risks, firms plan to do production in-house near key markets, work with local partners or outsource non-core work to distant locations. Some have gone away from far-off suppliers and are using nearshore or in-house models. Moving production closer reduces delay/improves control. For non-core products, outsourcing to offshore locations is still common but some companies set up offshore centres to manage operations directly. Changing supply chains to cope with delays and risks requires better forecasting tools, better data systems and trained people. Firms work with partners, rely on digital systems and have the right setup for various products. Global medicine supply chains must respond quickly to changes while reducing costs and maintaining product flow constant. Global health needs require clear strategy, simple design and fast action. Study survey was conducted among 218 people from supply chain department of pharmaceutical industry to know the factors that show the complexity and challenges of supply chain in pharmaceutical industry and found that Regulatory Compliance, Cold chain, Long Supply Chains, and Product shelf life are the factors that show the complexity and challenges of supply chain in pharmaceutical industry.

Designing transportation networks — as one of the most important decision problems in supply chain management — has become the focus of research attention in recent years. This paper introduces a framework which deals with the design of a transportation strategy for pharmaceutical supply chains. It consists of three steps: (i) identifying the configuration of the current distribution network, (ii) designing an optimal distribution network while determining the appropriate location-allocation decisions, and (iii) choosing the most appropriate transportation network strategy through the application of a multi-criteria decision analysis method (MCDA). The proposed framework is illustrated in designing a transportation network strategy for the Moroccan pharmaceutical products supply chain.

The need to implement and guarantee effective item-level tracing systems is becoming more and more important for a wide range of business applications, such as manufacturing, logistics, healthcare, and anti-counterfeiting. Among these, the pharmaceutical supply chain, with millions of medicines moving around the world and needing to be traced at item level, represents a very interesting reference scenario. Furthermore, the growing counterfeiting problem raises a significant threat within the supply chain system. Recently, several international institutions (e.g. Food and Drug Administration, European Medicines Agency, European Federation of Pharmaceutical Industries and Associations, GS1) are encouraging the use of innovative solutions in healthcare and in the pharmaceutical supply chain, to improve patient safety and enhance the efficiency of the pharmaceutical supply chain, with better worldwide drug traceability (FDA, 2004). Currently, the most popular auto-identification technology is optical one. Although the bar code (oneor bi-dimensional) is a very low cost solution, there are many valid reasons for not considering it as the primary auto-identification technique (Schroeter, 2008) in the near future. In fact, every kind of bar code technology requires line-of-sight (LoS), it cannot be written or read in bulk, it can be easily counterfeited, it can limit the speed of packaging line operations, etc. On the contrary, RFID (Finkenzeller, 2003) technology promises to optimize the critical processes in the Supply Chain Management (SCM) systems and to improve the patient safety, resolving problems of traditional optical auto-identification solutions. Passive RFID tags can be classified according to the frequency band used and the type of coupling between tag and reader antennas. The use of RFID solutions, in particular those working in Ultra High Frequency (UHF) band, could easily exceed the previous performance problems justifying the initial investment required by a process re-engineering of the pharmaceutical supply chain. Recent works (Uysal, 2008; De Blasi, 2010; Catarinucci, 2010) have highlighted that passive UHF RFID tags represent the more suitable solution for item-level tracing systems in a supply chain. Another fundamental element that is increasing exponentially the diffusion of the RFID in the automate logistics processes is the asserting of some international standards related to goods traceability, such as EPCglobal (Barchetti, 2009; Thiesse, 2009), GS1 (Global Standard 1) (Barchetti, 2010) and ebXML (Electronic Business using extensible Markup Language) (Barchetti, 2010), which are just a few interesting examples. The EPCglobal consortium,

The pharmaceutical supply chain is uniquely complex, characterized by high demand variability, stringent regulatory requirements, and the need for precise inventory control to ensure patient safety and therapeutic effectiveness. Traditional forecasting methods, while useful, often fail to cope with the dynamic nature of pharmaceutical supply chains. Enterprise Resource Planning (ERP) systems have long been central to managing operational data; however, their potential remains underutilized when not integrated with advanced data analytics capabilities. This proposes a conceptual model that integrates ERP systems with data analytics tools to enhance forecasting accuracy and supply chain responsiveness in the pharmaceutical sector. The model leverages ERP's comprehensive data capture across procurement, production, sales, and inventory modules, channeling this data through an analytics engine powered by machine learning and statistical algorithms. The proposed architecture includes key components such as a data ingestion layer, a preprocessing and transformation module, predictive analytics frameworks, and decision support interfaces. By integrating historical trends, real-time data, and external variables such as market dynamics and epidemiological patterns, the model supports predictive and prescriptive forecasting capabilities. A feedback mechanism is embedded to facilitate continuous learning and improvement, enabling the model to adapt to shifting patterns in demand and supply. This conceptual framework emphasizes modularity and scalability, supporting deployment across varying organizational contexts—from local distributors to global pharmaceutical manufacturers. Implementation considerations include data governance, regulatory compliance, IT infrastructure readiness, and cross-functional coordination. Ultimately, this integrated ERP–analytics approach aims to minimize stockouts, reduce overproduction, and improve overall supply chain efficiency. The model also provides a foundation for future enhancements such as IoT integration for real-time tracking and blockchain for transparency. This work contributes to the growing need for intelligent, adaptive supply chain systems and offers a pathway toward digital transformation in pharmaceutical logistics and forecasting.