1.1 Research Aim, Objectives and Research
This research aims to cover the gap in the literature and analyse the role of 4.0for the pharmaceutical supply chain in the UK
To analyse the use of 4.0in the supply chain networks of the pharmaceutical sector
To understand its importance in streamlining and shaping the supply chain networks
To identify its role for pharmaceutical businesses for supply chain collaboration
1. What is the role of 4.0in streamlining the supply chain networks of the pharmaceutical sector in the UK?
2. How the use of 4.0facilitates more agile, smart, and personalised pharmaceutical supply chains?
3. How 4.0can help pharmaceutical manufacturers maintain an end-to-end collaboration with all supply chain partners?
Chapter 2: Literature Review
2.1 Chapter Overview
The phrase "industry 4.0" (4.0) refers to the fourth industrial revolution. It designates a new level in the industrial value chain's structure and control. I4.0 is centred on cyber-physical systems (e.g.,'smart machines.') They are outfitted with modern control mechanisms, embedded software, and an Internet address, enabling them to communicate with and be addressed via the Internet of Things. The phrase "industry 4.0" relates to the "intelligent networking" of industrial equipment and processes via the use of information and communication technology.
Thus, commodities and industrial processes become networked and communicative, enabling novel forms of production, value creation, and real-time optimization. Smart factories are made possible by cyber-physical systems. These are the same features as the Industrial "Internet of Things", like remote monitoring and tracking and tracing. 4.0 is described as a phrase that refers to the modern trend of automation and data exchange in manufacturing technology, which includes "cyber-physical system", the "Internet of things", "cloud computing", and "cognitive computing", and the evolution of the smart factory.
The following portion of the literature review examined the 4.0trends in business, the benefits and impact of the 4.0trends on the pharmaceutical supply chain network, and the usage of 4.0 in UK pharmaceutical businesses. 4.0 is accelerating communication between producers and supply chain partners, but there are still hurdles stopping organisations from maximising supply chain potential. 4.0 and utilisation of the Digital Supply Chain Model in 4.0 to overcome Barriers were also painstakingly analysed to have a deeper understanding of the circumstances around the subject of the research.
2.1.1 Conceptual Framework
The literature review, based on what has been explained above, would be conducted following the conceptual framework below:
Fig 1: Conceptual Framework of Literature Review
(As created by author)
2.2 4.0Trends and Technology in Businesses
Industry 4.0 causes disruption and requires organisations to reconsider their supply chain strategy. Khan et al (2021) indicated that supply chains can reach the next stage of operational efficiency and utilise developing business models of the digital supply chain into digital supply networks. Such a need to shift is vital more than ever, as big trends and consumer requirements change the situation. Chhetri et al (2018) have expressed an opinion that many macro trends have an impact on the supply chain management (SCM), such as rural areas worldwide continue to increase and wealth shifting in regions previously overlooked. Responsibility to minimise carbon emissions along with traffic regulations for socio-economic considerations complements the issues facing logistics.
Oztemel and Gursev (2020) remarked, however, the shifting population figures also limit labour supply and increase ergonomic demands as a result of increasing employee age. Online transparency and convenient access to a variety of shopping and buying options fuel the competition of supply chains. Consumer needs and expectations are expanding at the same time and online trends in recent years have led to higher service-related expectations, along with stronger “granularisation” of orders (Alicke, Rexhausen and Seyfert, 2017). In addition, the robust expansion and continued changes in the organisational portfolio are driven by a marked tendency for additional individualization and adaptation. Supply chains need to be much quicker, much more accurate and more granular to build on such trends and to meet the changing needs. Thus, Ghadge in his works with other scholars, have detailed the technologies of 4.0and their role in businesses as follows:
Augmented Reality: As per Vaidya, Ambad and Bhosle (2018), several services may be obtained using AR systems, for example, creating an arrangement in a warehouse or manufacturing line and transmitting repair directions by mobile or other remotely controlled devices. Nevertheless, organisations will, in the future, make a far larger revolution in AR to enhance their business and decision-making. Such systems are presently in their early phases.
Cloud Technology: In terms of using remote servers known as cloud systems, large volumes of information collected from several commercial systems, equipment, devices and sensors is stored, as per Oztemel and Gursev (2020). This technology offers real-time accessibility and retrieval of huge parts of data. Upgraded data exchange is required throughout organisational units, value chains, sites and corporate/organisational boundaries. In cloud computing settings, more data-driven as well as intelligent SC activities develop quickly and drive them.
The Industrial Internet of Things (IIoT): 4.0is an IIoT platform, which interacts and communicates with various equipment and systems as a centralised control system (Gunasekaran, Subramanian and Tiwari, 2016). The IIoT permits for traceability and follow-up in real-time with decentralised evaluation along with decision-making. Coherent cross-organisational collaboration through the IIoT will allow entirely automated value chains and therefore enhance the business and functional capacities of organisations.
Big Data Analytics: The utilisation of large amounts of data to enhance efficiency and production is allowed by big data analytics. Ghobakhloo (2018) stated that this allows companies to gain value from massive amounts of data for improvement in operational efficiency and performance, flexibility and agility as well as product customisation. The activity of collection and analysis of data from various systems is the norm that makes decision making in real-time and fast based on facts.
Autonomous Robots: The technology of robotics nowadays is utilised in a wide variety of fields, including production, logistics, e-commerce, education, etc. (Ghadge et al, 2020). The robots eventually began interacting and working securely with the operators and helping the operators side by side. These robots are projected to be more affordable and offer a larger variety of capacities in the future than now utilised.
Cybersecurity: Increasing the risk of cybersecurity with the adoption of Industry 4.0. Safe, dependable communication and advanced identification and access control may be achieved, according to Ghadge et al (2019). The sustainability of 4.0systems is a critically needs cybersecurity, and cybersecurity policies should thus be linked with enterprises’ information technology systems.
Additive Manufacturing: Additive manufacturing and 3D printing are utilised in different layers of three-dimensional objects (Ghadge et al, 2018). The new technologies for manufacturing in small batches of custom-made items offering productivity gains are frequently employed with I4.0.
Business Intelligence (BI): Ghadge et al (2020) have further stated that BI is a technology framework for collecting, analysing, storing and presenting information from many sources. Through turning raw corporate information into relevant and valuable knowledge and information, this aids decision-making.
Simulation: Simulation is extensively employed in commercial models to use existing real-time data and recreate the working environment in a virtual ecosystem, as opined by Zhong et al (2017). Simulation process testing and optimisation enable individuals to decrease business change, risks, time setup and improve quality control in future operations. To analyse all potential product design, development, manufacturing and SC networks scenarios, the data processed and obtained from cloud systems and Big Data may be utilised as a virtual model feed.
2.2.1 Benefits and Impact of 4.0Trends on Pharmaceutical Supply Chain Networks
Scholars, including the ones mentioned above, have opined that supply Chain 4.0 would affect all SCM domains. Various models have been designed to organise the key Supply Chain 4.0 improvements and relate them to six main values. In the end, improvement in this area enables service, expense, capital and agility to be changed systematically. The notion of 4.0is an industrial approach, which covers all areas of an industrial operating framework such as culture, management and engagement with regulatory bodies. According to Reinhardt, Oliveira and Ring (2021), I4.0-stronger trends, including design data integrity, holistic control methods, tailored treatments, and end-to-end supply incorporation throughout the industry, have transformed production from mass manufacturing to mass customisation. I4.0’s developing technologies allow the production of sustainable values and lead to more flexible, intelligent and customised pharmaceutical industries, thereby giving pharmaceutical firms competitive advantages. Ding (2018) have opined in this aspect that to fit future operations and management of the pharmaceutical goods throughout the life cycle, more sustainability in pharmaceutical supply chains should be established. For instance, the 4.0technologies enhance the smooth and highly efficient integration of the delivery chain of any business end-to-end. It boosts productivity and provides the organisation with instant advantages (Alicke, Rexhausen and Seyfert, 2017). Nevertheless, it is also simpler to create a more connected and efficient supply chain that offers new commercial prospects.
For almost 20 years, the concepts of AR, along with virtual reality (VR) have persisted, but only lately they have infiltrated the corporate world, as Reinhardt, Oliveira and Ring (2021) have further stated. These 4.0technology applications in the pharmaceutical industry help firms to minimise design and manufacturing expenses, preserve product quality and shorten the time needed for moving from product to production idea. As an aid to industrial applications, AR is acknowledged, which includes product assembly, improved quality and efficiency of assembly and reduced assembly and maintenance expenses, based on another research of Reinhardt, Oliveira and Ring (2020). AR visualisation tools need, however, be enhanced to enable smooth and comprehensive production integration, as the existing technology is not appropriate for continuing usage and demanding working conditions, such as those in the pharmaceutical sector.
3D printing offers a way to create solid oral doses, including complex modification release in items, via stacking of tiny polymer strands to make a personalised and reproducible unit rapidly and efficiently, as stated by Jamróz et al (2018). It would therefore become a major technology in production, with improved characteristics and complicated and lightweight designs of personalised products and sophisticated items. Decentralized additive manufacturing systems with high performance significantly minimise transport distances and inventory on hand. The topic of customised treatments is intrinsically related to 3D printing and additive production. With the specific production of each unit, 3D printing can enable manufacturers to get comprehensive controls, including additional parameters about the dose, material utilised or product construction (Ali, Ahmad and Akhtar, 2020). 3D printing may thus be enhanced to include pre-clinical development, clinical trials and frontline medical treatment throughout the drug development process.
Furthermore, the contemporary production system is connected by an Internet of Things (IoT) and has cyber, cyber-physical and human components. Kumar et al (2020) have stated that IoT influences control on quality, traceability of supply chains and overall efficiency of the supply chain. This guarantees product integrity and traceability throughout the entire supply chain network. Collectively, 4.0and cloud manufacturing own the capacity to unleash the pharmaceutical sector’s full potential. Big data analysis and IoT support businesses in anticipating and shaping future client needs, therefore making the delivery of final products more efficient.
2.3 Use of 4.0in UK Pharmaceutical Businesses
A leading participant in the UK is the pharmaceutical sector. In 2017, there was an annual revenue of more than 42 billion British pounds for pharmaceutical wholesalers, as Stewart (2020) states, whereas in 2017 the net capital investment for the production of pharmaceutical products amounted to over a billion. Furthermore, the UK has an ageing population since the healthcare system is improving and increasing. Consequently, pharmaceutical businesses are broadening their scope and activities. Nevertheless, when the supply chain network gets bigger, an effectual collaboration between industries or organisations becomes more challenging (Sarkis et al, 2021). The pharmaceutical sector is one of three technology-oriented sectors in the UK, where the patent is almost equivalent to the products. The other industries include the chemical and biotechnology industries. These are prospects to sell to UK pharmaceutical firms for organisations with supply chain expertise. Pharmaceutical producers in the UK expect expanded EU operations to secure access to supply chain and markets in the scenario of hard Brexit (Myllylä, 2020). Pharmaceutical production may truly profit from supply chain 4.0 in a sector, which depends significantly on the collection of data to monitor quality, output, screening, storage and distribution.
2.4 4.0Driving Collaboration between Manufacturers and Supply Chain Partners
Industry 4.0 is rapidly changing the way organisations handle their most critical activities. Digitalisation — aided by disruptive “new technologies” such as the “Internet of Things”, “artificial intelligence”, “big data” and “analytics”, “machine learning”, “automation” and “robotics”, “cloud computing”, “blockchain”, “3D printing”, and other emerging technologies, as well as the explosive growth of smart devices — is affecting every sector of the business (Manavalan and Jayakrishna, 2019). SCM, which has become more complicated than ever before, stands to gain greatly from the use of digital technologies. Based on current research, companies can reduce operational costs by more than 30%, lose “sales opportunities” by more than 60%, and even “inventory requirements” by more than 70% when their supply chains are consistent and digital. At the same time, companies can become faster, more agile and accurate while increasing efficiency (Luthra et al., 2020). While transforming a supply chain into one that is digital, automated, and completely networked will take substantial effort and long-term expenditures, the benefits will be enormous. Businesses can achieve the next level of operational performance while also seeing considerable cost reductions by bringing their supply chains online.
Supply Chain 4.0 integrates detectors into everything, establishes networks everywhere, automates machines, and analyses data to enhance customer experience and satisfaction. The way forward is to embed sensors in everything, to build networks all over the place, to automate and to analyse the whole thing in order to pointedly improve efficiency and purchaser fulfilment (Türke? et al., 2019). Over the last three decades, logistics has progressed from an exclusively integrated process reporting to sales or manufacturing and directly responsible for maintaining the supply of production lines and delivering goods to customers to an independent supply chain management function directed by a “CSO” (“Chief Supply Chain Officer”) in some organisations. “ SCM has shifted its emphasis in recent years to advanced planning procedures like “analytical demand planning” and “integrated supply chain planning”, that have become established trade methods in several organisations, whereas “operational logistics” has increasingly been outsourced to “third-party logistics service providers” (LSPs). 2019 (Tang and Veelenturf).
2.5 Barriers Preventing the Businesses from Leverage Full Potential of Supply Chain 4.0
Despite the allure of collaborative supply chain efforts, organisations that collaborate on strategic supply chains tend to encounter hurdles (Ali and Aboelmaged, 2021). These roadblocks exist at three organisational levels: "intra-organizational", and "inter-organizational". For example, strategic supply chains may experience performance "glitches" or a failure to meet customer requirements as a consequence of issues like quality and manufacturing issues, employee aversion to relinquishing control, and insufficient collaborative planning. These might be highly expensive in terms of increased inventory and slower sales growth. These potentially costly consequences of failing to satisfy customer needs are a compelling incentive to deploy the SCM. Despite rising interest in SCM and the related advantages, difficulties, and possibilities for success, multi-channel research mitigating all three issues is essential. Identifying how, when, and why certain supply networks thrive while others fail would be beneficial not just for supply chain academics, but also for managers charged with the everyday task of executing strategic supply chain management.
To guarantee the effective adoption of strategic supply chains, organization must identify obstacles and bridges holistically, react to eventualities, and manage the supply chain pro-actively. Strategic supply networks are supply chains that are "strategic, operational, and technologically integrated" and are designed to have long-term stable connections that can adapt to changing environmental conditions. In summary, when strategic supply chains as management of the organisation are capable of adapting to and connecting with external market needs, they have a greater chance of success. Nonetheless, businesses do have options and the potential to overcome these barriers. Partners in strategic supply chains can develop and implement efforts that bridge the divide between a “supply chain” and a “strategic supply chain” (Culot et al., 2020). " Individual empowerment", "information integration", and alliance development are just a few of these bridges. Therefore, strategic supply chains may add value if they are capable of coping with competing needs via a variety of methods. SCM is motivated by external forces and the "potential benefits" of strategic SC synchronisation. External limitations include technology developments and growing customer demand across national borders; cost minimization in order to fulfil these different needs; and enhanced efficiency as a consequence of vertically integrated business linkages.
The dynamics have begun to shift the emphasis away from the individual businesses vying for large market share and dominance and toward supplier networks vying for market share and dominance. Numerous advantages exist for strategic SCM. The expected advantages of good SC collaboration are the second main incentive (Ghadge et al., 2020). To enable SC managers to make challenging decisions in various situation, critical data should be available at the right time and in the correct place. Management should be able to “think outside the box” while handling SC challenges through the use of varied approaches and individuals. To summarise, external constraints push businesses to align and build strategic supply networks that are environmentally responsible (Raj et al., 2020). Numerous advantages accrue to businesses who collaborate on SC by bringing their behaviour into alignment with the environment. To realise these aids, strategic supply chains must transcend “barriers to collaboration” via the use of a range of “approaches” and “strategies” that perform as bridges.
2.5.1 Use of Digital Supply Chain Model in 4.0to Bridge the Barriers
The digitalisation of SCs is not mainly attributable to the deployment of online and offline digitalisation in “network structures” or communication and “information technology systems” of traditional SCs; rather, the transformation necessarily requires special attention (Khan et al., 2021). The DSC model idea offers an outline for the implementation and amalgamation of current and upcoming 4.0technology enablers and capabilities into existing SCMs, therefore facilitating their transformation into a digitalized SCM. This technique is presented within a multidimensional and interconnected framework, along with the resulting “technological” and “managerial implications”: Innovation, creative change, and the fast adoption of new 4.0technologies all point to an approaching revolution and development of SCMs toward digitalisation. Failure to adapt to this change may jeopardise business models, causing them to become mired down in the adoption and deployment of technology enablers and eventually succumbing to extinction. To improve SC performance (“cost, quality”, “flexibility”, and “timeliness”), integration on several levels is required: “internal/external integration”; “functional integration”; “geographical integration”; “chain and network integration”; and “information technology integration”.
5 essential factors are required for the successful implementation of “4.0 technology into DSCs”: the deployment of 4.0technology enablers and features human-technology relationships in digital SCMPs; project management to digitally transform and manage organisational behaviour in SCMCs and the establishment of technological infrastructure or a physical and digital SCNS. By becoming more digital and data-driven, SCs may be able to provide benefits to their consumers. Each actor in the value chain is willing to abandon a linear view of the relationship between every actor and the SC structure in favour of advancement as a “multi-dimensional” organisational strategy for the DSC’s transparency, flexibility, cooperation, “real-time responsiveness”, precision, and communication.
To provide businesses with the complete “DSC experience”, a decent number of procedures will need to be transformed into virtual and intelligently automated. As more firms embrace this new way of doing business, those that retain an excessive number of manual procedures risk falling behind. Because of digitization, the entire SC structure is altering (Gupta et al., 2020). As a result of the proposed architecture, a unique visual representation of the current activities of "directed networked SCs" in "globally integrated clusters" is conceivable. DSCs driven by cloud computing have new difficulties that require them to achieve unprecedented levels of visibility, intelligence, and agility while working rapidly and effectively (Attaran, 2020). Due to the loss of control over data that was previously stored on "internal servers" and/or "computer hard drives", the security of this data on the web and in the event of a service failure also offers significant problems.
“Multiple DSCs” and their “clusters” would be responsible for the actual integration of various smart factories, as well as an even greater degree of global integration, expertise, and real-time information. The virtual world will develop from the real one, but will share the digital world’s predictive capabilities, varied intellect, and interconnectivity (Ivanov and Dolgui, 2020). Each element of the DSC model is already speeding the integration, connectivity, and high added value revolution in 4.0and a digital and smart world for final customers, and internal suppliers and customers. As a result of this visualisation and current “state of the DSCs”, a critical stage is recognising the growth phases that advance from internal integration and growth to external integration – toward main objective network SC and DSC management – in order to accomplish progression for “collaborative DSC clusters” (Agrawal and Narain, 2018). However, the aforementioned concept can be realised only by moving away from a single linear SC and toward continually changing integrated DSC networks as a consequence of multiple industrial automation in a connected world (Büyüközkan and Göçer, 2018).
SCMCs are actively being developed, both in established SCs and in emerging and digitalized SCs. It would have a substantial impact to be capable of conducting field research on new constructs while relating to the “reconfiguration of logistical processes” and supply chain management, the administrative structure, the flows, and also the new “physical” and “digital performers” capable of implying key management positions and even implementing new technological and digital structures. By contrast, the digital supply chain compresses into a dynamic, integrated supply network as each supply point becomes more capable and connected (Garay-Rondero et al., 2019). Digital Supply Chain Networks (DSNs) overcome the linear supply chain’s delayed action-reaction cycle by leveraging real-time data to enhance decision-making, boost transparency, and enable improved collaboration throughout the whole supply chain. It is important to realise the shift from a traditional supply chain to a single DSN. The proposed DSC model for 4.0 is made up of six inextricably linked dimensions: supply chain production practises (SCMPs) and “supply chain management” centres (SCMCs), “supply chain networks” (SCNs), 4.0 technology enablers and characteristics, flow, “virtual value creation” (resulting in the “virtual value chain”), and the online and offline world in general. These “dimensions” interrelate continually within a “physical SC” and a “virtual SC”, designated to as the “physical SC” and “virtual SC scopes”, respectively.
The DSC model’s primary objective is to establish a framework for the new digitalized SCs that are emerging as a result of I4.0’s advancement of daily activities (Papadonikolaki, 2020). Not only does the digital value chain illustrate the dynamic nature of value creation, but it also demonstrates the emergence of new commodities and services in an information-driven economy. Using this approach as a baseline, the primary outcome of any DSC is the production of virtual value via the newly suggested model’s two constructs, CC and Cloud Robotics (CR). Only with this robust intelligence will it be possible to appreciate the value of availability (making a service or product available to users via autonomous delivery), the significance of digital servitization (the availability of a variety of IT-based services that go beyond simple product distribution or physical service provision), and the significance of “digital integration” (which results from permeable transparency).
2.6 Literature Gap
Holding the hand of I4.0, an increasing need is prominent in the academic research on the execution of this technological revolution in supply chain networks. Keeping the importance of 4.0in mind, and its extensive impact on the supply chain networks of businesses of this time, as well as the significance of the pharmaceutical industry in the UK, robustness in literary researches, is of utmost importance to understand this massive industrial revolution and how it is going to affect different sectors. However, this research is focused on analysing this industrial revolution phase in terms of the pharmaceutical industry, where the gap has been found while reviewing the literary opinions and concepts on the barriers that hinder the 4.0implication in full potential by the pharmaceutical businesses. Furthermore, the background study has found that the literary works are based on the use of 4.0in the overall business operations of pharmaceutical companies, though a lack of data has been observed in concentrating on the discussion of these technologies in the SCM. Apart from that, regional data on this subject matter is not an easy task to find among the works of scholars and experts. Moreover, the significant role of this industry-wide technological implication in the SCM of the UK-based pharmaceutical businesses has not been much focused on at all.
The pharmaceutical sector is always looking for methods to enhance procedures. Businesses can update the data accumulation and analysis by implementing Supply Chain 4.0. It can increase communication and streamline the production process from start to end in detail. The major impact of supply chain 4.0 on manufacturing is the capacity to increase efficiency in processes. The supply chain depends on how consumer demand is predicted and fulfilled as precisely as feasible. With the introduction of new software and tools, manufacturers can put other data into the mix, like economic statistics and health patterns, to make the estimations more precise.
Chapter 2: Literature Review
Agrawal, P. and Narain, R., 2018, December. Digital supply chain management: An Overview. In IOP Conference Series: Materials Science and Engineering (Vol. 455, No. 1, p. 012074). IOP Publishing.
Ali, A., Ahmad, U. and Akhtar, J., 2020. 3D printing in pharmaceutical sector: An overview. Pharmaceutical Formulation Design-Recent Practices.
Ali, I. and Aboelmaged, M.G.S., 2021. Implementation of supply chain 4.0 in the food and beverage industry: perceived drivers and barriers. International Journal of Productivity and Performance Management.
Alicke, K., Rexhausen, D. and Seyfert, A., 2017. Supply Chain 4.0 in consumer goods. Mckinsey & Company, pp.1-11.
Attaran, M., 2020, July. Digital technology enablers and their implications for supply chain management. In Supply Chain Forum: An International Journal (Vol. 21, No. 3, pp. 158-172). Taylor & Francis.
Büyüközkan, G. and Göçer, F., 2018. Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, pp.157-177.
Chhetri, S.R., Faezi, S., Rashid, N. and Al Faruque, M.A., 2018. Manufacturing supply chain and product lifecycle security in the era of I4.0. Journal of Hardware and Systems Security, 2(1), pp.51-68.
Culot, G., Orzes, G., Sartor, M. and Nassimbeni, G., 2020. The future of manufacturing: A Delphi-based scenario analysis on I4.0. Technological forecasting and social change, 157, p.120092.
Ding, B., 2018. Pharma I4.0: Literature review and research opportunities in sustainable pharmaceutical supply chains. Process Safety and Environmental Protection, 119, pp.115-130.
Garay-Rondero, C.L., Martinez-Flores, J.L., Smith, N.R., Morales, S.O.C. and Aldrette-Malacara, A., 2019. Digital supply chain model in I4.0. Journal of Manufacturing Technology Management.
Ghadge, A., Kara, M.E., Moradlou, H. and Goswami, M., 2020. The impact of 4.0implementation on supply chains. Journal of Manufacturing Technology Management.
Ghadge, A., Karantoni, G., Chaudhuri, A. and Srinivasan, A., 2018. Impact of additive manufacturing on aircraft supply chain performance: A system dynamics approach. Journal of Manufacturing Technology Management.
Ghadge, A., Weiß, M., Caldwell, N.D. and Wilding, R., 2019. Managing cyber risk in supply chains: A review and research agenda. Supply Chain Management: An International Journal.
Ghobakhloo, M., 2018. The future of manufacturing industry: a strategic roadmap toward I4.0. Journal of Manufacturing Technology Management.
Gunasekaran, A., Subramanian, N. and Tiwari, M.K., 2016. Information technology governance in Internet of Things supply chain networks. Industrial Management & Data Systems.
Gupta, S., Modgil, S., Gunasekaran, A. and Bag, S., 2020, July. Dynamic capabilities and institutional theories for 4.0and digital supply chain. In Supply Chain Forum: An International Journal (Vol. 21, No. 3, pp. 139-157). Taylor & Francis.
Ivanov, D. and Dolgui, A., 2020. A digital supply chain twin for managing the disruption risks and resilience in the era of I4.0. Production Planning & Control, pp.1-14.
Jamróz, W., Szafraniec, J., Kurek, M. and Jachowicz, R., 2018. 3D printing in pharmaceutical and medical applications–recent achievements and challenges. Pharmaceutical research, 35(9), pp.1-22.
Khan, S.A., Kusi-Sarpong, S., Gupta, H., Arhin, F.K., Lawal, J.N. and Hassan, S.M., 2021. Critical factors of digital supply chains for organisational performance improvement. IEEE Transactions on Engineering Management.
Khan, S.A., Naim, I., Kusi-Sarpong, S., Gupta, H. and Idrisi, A.R., 2021. A knowledge-based experts’ system for evaluation of digital supply chain readiness. Knowledge-Based Systems, 228, p.107262.
Kumar, S.H., Talasila, D., Gowrav, M.P. and Gangadharappa, H.V., 2020. Adaptations of Pharma 4.0 from I4.0. Drug Invention Today, 14(3).
Luthra, S., Kumar, A., Zavadskas, E.K., Mangla, S.K. and Garza-Reyes, J.A., 2020. 4.0as an enabler of sustainability diffusion in supply chain: an analysis of influential strength of drivers in an emerging economy. International Journal of Production Research, 58(5), pp.1505-1521.
Manavalan, E. and Jayakrishna, K., 2019. A review of Internet of Things (IoT) embedded sustainable supply chain for 4.0requirements. Computers & Industrial Engineering, 127, pp.925-953.
Myllylä, J., 2020. The impact of the post-referendum period on the trade between the United Kingdom and the European Union.
Oztemel, E. and Gursev, S., 2020. Literature review of 4.0and related technologies. Journal of Intelligent Manufacturing, 31(1), pp.127-182.
Papadonikolaki, E., 2020. The digital supply chain: mobilising supply chain management philosophy to reconceptualise digital technologies and building information modelling (BIM). Successful Construction Supply Chain Management: Concepts and Case Studies, pp.13-41.
Raj, A., Dwivedi, G., Sharma, A., de Sousa Jabbour, A.B.L. and Rajak, S., 2020. Barriers to the adoption of 4.0technologies in the manufacturing sector: An inter-country comparative perspective. International Journal of Production Economics, 224, p.107546.
Reinhardt, I.C., Oliveira, J.C. and Ring, D.T. 2021. 4.0and the Future of the Pharmaceutical Industry.
Reinhardt, I.C., Oliveira, J.C. and Ring, D.T., 2020. Current perspectives on the development of 4.0in the pharmaceutical sector. Journal of Industrial Information Integration, 18, p.100131.
Sarkis, M., Bernardi, A., Shah, N. and Papathanasiou, M.M., 2021. Emerging Challenges and Opportunities in Pharmaceutical Manufacturing and Distribution. Processes 2021, 9, 457.
Stewart, C. 2020. Pharmaceutical industry in the United Kingdom (UK) - Statistics & Facts. [online] Available at: https://www.statista.com/topics/5056/pharmaceutical-industry-in-the-uk/#topicHeader__wrapper [Accessed on: 13th September, 2021]
Tang, C.S. and Veelenturf, L.P., 2019. The strategic role of logistics in the 4.0era. Transportation Research Part E: Logistics and Transportation Review, 129, pp.1-11.
Türke?, M.C., Oncioiu, I., Aslam, H.D., Marin-Pantelescu, A., Topor, D.I. and C?pu?neanu, S., 2019. Drivers and barriers in using I4.0: a perspective of SMEs in Romania. Processes, 7(3), p.153.
Vaidya, S., Ambad, P. and Bhosle, S., 2018. I4.0–a glimpse. Procedia manufacturing, 20, pp.233-238.
Zhong, R.Y., Xu, X., Klotz, E. and Newman, S.T., 2017. Intelligent manufacturing in the context of I4.0: a review. Engineering, 3(5), pp.616-630.