Organization Theory Perspective of Supply Chain Management 4.0: A Technological Paradigm Shift within the UK Manufacturing Sector.

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1.0 Introduction

1.1 Research Aim and Objectives

Research Aim

To analyse this paradigm shift and the application of Organization Theory perspectives of “Supply Chain Management 4.0” through the lens of several organization theory perspectives by the integration of advanced technologies and digitalization into the supply chain processes.

• To evaluate how internal capabilities, including technology infrastructure, data analytics, and workforce skills, affect the competitive advantage of organizations implementing SCM 4.0 in the UK Manufacturing Sector.

1.2 Research Questions

• How do Industry 4.0 technologies impact supply chain performance in the UK Manufacturing Sector?

2.0 Literature Review

2.1 Evolution of Supply Chain Management 4.0

An expanding circular economy: The goal of the production and consumption paradigm known as the circular economy is to reduce or eliminate waste and pollution. More sustainable and robust supply chains may be built with the help of SCM 4.0 technology (Chauhan et al., 2022). Cybersecurity's growing significance: Supply chains are more susceptible to cyberattacks as they become more digitalized and networked. To safeguard their supply chains from cyberattacks, businesses are investing on cybersecurity solutions.

2.2 Technological Advancements in “Supply Chain Management 4.0”.

“Supply Chain Management 4.0” (SCM 4.0) is a set of technologies that helps firms improve their supply chain management. Businesses may increase their profits and competitiveness by adopting these technologies.

Big data and analytics: In order to better understand supply chain performance, spot patterns, and foresee disruptions, businesses are turning to big data and analytics (Darvazeh, Vanani and Musolu, 2020).

Blockchain: The usage of blockchain technology in the supply chain has increased visibility and traceability.

2.3 Classical management theories and its relevance to “Supply Chain Management”.

• Administrative structure based on formalised processes and a strict chain of command.

Traditional management ideas have been called out for being overly set in their ways. They do, however, remain useful in a variety of supply chain management contexts. The scientific management idea of specialisation is one example that has proven useful in the field of supply chain management. Supply chain experts may maximise their effectiveness by honing their skills in certain areas. Supply chain management relies heavily on the administrative management philosophy of unity of command. Having a defined chain of command helps keep everyone on the same page and prevents arguments about who is accountable for what. Standardisation is an important concept in both bureaucratic administration and supply chain management. Supply chains may function more effectively and dependably if processes and procedures are standardised.

2.4 Application of Classical Management Theories in Modern Supply Chain Practices.

Amazon: Amazon optimises its supply chain with the use of scientific management practises. Robots are used to automate work in the company's warehouses, and algorithms are used to determine the most efficient routes for transporting products.

Walmart: Walmart's supply chain is designed and structured according to the concepts of administrative management (Min, Zacharia and Smith, 2019). For instance, it may use a centralised distribution system to save money and boost productivity.

2.5 Impact of Supply Chain Management 4.0 on Organizational Structures.

The term "Supply Chain Management 4.0" (SCM 4.0) is used to describe the incorporation of data analytics, enhanced automation, and digital technologies into the supply chain management framework (Zekhnini et al., 2020). This method employs cutting-edge tools like the “Internet of Things (IoT)”, “artificial intelligence (AI)”, “big data analytics”, and blockchain to improve supply chain performance. The effects of SCM 4.0 on corporate architectures are far-reaching and complex.

Flatter Hierarchies: In SCM 4.0, conventional organisational hierarchies are often dismantled (Plekhanov, Franke and Netland, 2022). The availability of real-time data and automated decision-making processes will reduce the need for micromanagement.

Supplier and Partner Relationships: Increased supplier and partner collaboration is seen. Collaboration, transparency, and traceability are all made possible in real time by SCM 4.0. This has the potential to pave the way for the development of networked organisational structures in which many participants in a supply chain ecosystem work together intimately.

Customization and Personalization: The level of product and service customisation made possible by SCM 4.0 is unprecedented (Dogru and Keskin, 2020). As a result, the company may have to form modular teams with specialised skills to meet the needs of its varied clientele.

3.0 Methodology

3.1 Research Philosophy

This research applies an interpretivism ethos to a study of “Industry 4.0 Supply Chain Management in the United Kingdom's” industrial industry. The goals of the research are consistent with interpretivism's focus on fully comprehending how organisations deal with the technological paradigm change in light of their own contexts, environmental constraints, and external forces (Kirongo and Odoyo, 2020). Qualitative research techniques, such as in-depth interviews and content analysis, allow for a deeper understanding of how organisations are adapting to the changing digital landscape by delving into employees' thoughts, feelings, and motivations.

3.2 Research Approach

In order to accomplish its goals, this study employs an inductive methodology. The incorporation of Industry 4.0 technology into supply chain management in the UK manufacturing sector is a complicated and novel phenomenon that lends itself well to inductive study (Mehrad and Zangeneh, 2019). The research will gather secondary data, often in the form of qualitative material, and analyse it to draw conclusions and provide explanations. Starting with concrete examples, it moves on to analyse and generalise facts and experiences about how businesses are adjusting to SCM 4.0.

3.3 Research Design

3.4 Data Collection Method

3.5 Data Analysis

Thematic analysis is used on secondary qualitative data to draw up important themes and patterns for this study. Various research papers, reports, case studies, and interviews will be used to compile the data on “Supply Chain Management 4.0” in the UK Manufacturing Sector. The data will be reviewed by the researcher to ensure accuracy and to eliminate any unnecessary or redundant information. Assigning descriptive codes to pertinent chunks of text or material, this procedure will be performed across all data sources. Similarities and relevance will be used to inductively develop themes (Lochmiller, 2021). Triangulation, in which different researchers independently examine the data to increase its validity and dependability, will be used for data validation. Any disagreements may be worked out via discussion and agreement. Findings will be recorded and their significance to the study goals will be explored, and the discovered themes and patterns will be organised into a cohesive narrative. The UK manufacturing sector is undergoing a technological paradigm shift, and our method provides a structured and methodical means to extract valuable insights into how businesses are coping with this change.

3.6 Ethical Considerations

The study investigates the moral implications of gathering secondary data. Privacy, confidentiality, permission for use, accuracy, completeness, provenance, attribution, referencing, originality, and transparency are all upheld. Data privacy refers to the practise of protecting the personal information of people and businesses whose records are compiled in secondary sources. Consent for the use of data guarantees that the terms and conditions established by the data's original providers are followed and that any necessary licences or permits are secured. Preventing modification or distortion that might lead to misunderstanding is crucial to maintaining data integrity and authenticity. It is essential to give acknowledgement to those whose work was used as a foundation for research. Plagiarism is avoided at all costs, and honesty is preserved by thorough documentation and reporting of the secondary data's origins, techniques, and analyses. By adhering to these ethical concerns, the research guarantees that it is performed with the highest ethical standards and expertise, protects the rights and privacy of data sources, and maintains the integrity of the secondary data collection process.

3.7 Research Limitation

6.0 Research Timeline

Table 1: Research Timeline

(Source: Self Developed)

7.0 Conclusion

References

Chauhan, S., Singh, R., Gehlot, A., Akram, S.V., Twala, B. and Priyadarshi, N., 2022. Digitalization of Supply Chain Management with Industry 4.0 Enabling Technologies: A Sustainable Perspective. Processes, 11(1), p.96. https://www.mdpi.com/2227-9717/11/1/96

Darvazeh, S.S., Vanani, I.R. and Musolu, F.M., 2020. Big data analytics and its applications in supply chain management. New Trends in the Use of Artificial Intelligence for the Industry, 4, p.175. https://library.oapen.org/bitstream/handle/20.500.12657/43835/1/external_content.pdf#page=189

HR, G. and Aithal, P.S., 2022. How to Choose an Appropriate Research Data Collection Method and Method Choice among Various Research Data Collection Methods and Method Choices During Ph. D. Program in India?. International Journal of Management, Technology, and Social Sciences (IJMTS), 7(2), pp.455-489. https://www.researchgate.net/profile/Ganesha-H-R/publication/365096704_How_to_Choose_an_Appropriate_Research_Data_Collection_Method_and_Method_Choice_Among_Various_Research_Data_Collection_Methods_and_Method_Choices_During_PhD_Program_in_India/links/6364b15637878b3e877e5c19/How-to-Choose-an-Appropriate-Research-Data-Collection-Method-and-Method-Choice-Among-Various-Research-Data-Collection-Methods-and-Method-Choices-During-PhD-Program-in-India.pdf

Khan, M.D., Schaefer, D. and Milisavljevic-Syed, J., 2022. Supply Chain Management 4.0: Looking Backward, Looking Forward. Procedia CIRP, 107, pp.9-14. https://www.sciencedirect.com/science/article/pii/S2212827122002189/pdf?md5=d2cf691ea944f730d5fb9489dd975402&pid=1-s2.0-S2212827122002189-main.pdf

Plekhanov, D., Franke, H. and Netland, T.H., 2022. Digital transformation: A review and research agenda. European Management Journal. https://www.sciencedirect.com/science/article/pii/S0263237322001219

Sobb, T., Turnbull, B. and Moustafa, N., 2020. Supply chain 4.0: A survey of cyber security challenges, solutions and future directions. Electronics, 9(11), p.1864. https://www.mdpi.com/2079-9292/9/11/1864/pdf