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Ahmed, H.F.; Hosseinian-Far, A.; Sarwar, D.; Khandan, R. Impact of Supply Chain Complexity on Knowledge Transfer. Encyclopedia. Available online: https://encyclopedia.pub/entry/55063 (accessed on 16 November 2024).
Ahmed HF, Hosseinian-Far A, Sarwar D, Khandan R. Impact of Supply Chain Complexity on Knowledge Transfer. Encyclopedia. Available at: https://encyclopedia.pub/entry/55063. Accessed November 16, 2024.
Ahmed, Hareer Fatima, Amin Hosseinian-Far, Dilshad Sarwar, Rasoul Khandan. "Impact of Supply Chain Complexity on Knowledge Transfer" Encyclopedia, https://encyclopedia.pub/entry/55063 (accessed November 16, 2024).
Ahmed, H.F., Hosseinian-Far, A., Sarwar, D., & Khandan, R. (2024, February 15). Impact of Supply Chain Complexity on Knowledge Transfer. In Encyclopedia. https://encyclopedia.pub/entry/55063
Ahmed, Hareer Fatima, et al. "Impact of Supply Chain Complexity on Knowledge Transfer." Encyclopedia. Web. 15 February, 2024.
Impact of Supply Chain Complexity on Knowledge Transfer
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The dynamics of supply chain networks have changed due to increasing complexities. Global expansions and knowledge transfer in supply chain networks bring efficiency and effectiveness to companies. However, the probability of supply chain complexity has also been seen increasing. The barriers to sustainable supply chain networks need to be tackled in an effective manner as they impact business operations. Therefore, it is essential to eliminate and reduce the supply chain complexities, as it will facilitate the process of knowledge transfer and increase the implementation of sustainable practises in supply chain networks.

supply chain complexity factors knowledge transfer sustainable supply chain networks process complexity

1. Introduction

Businesses at present are trying to adopt innovative strategies to cope with challenges and disruptive environments [1]. According to Del Giudice and Maggioni, firms should constantly update and enhance their learning processes, share information and knowledge, and create new information to cater to the difficulties [2]. Over the past 20 years, there have been several studies about the theory and practise of supply chain networks, but the area is still undergoing significant development and enhancement. The market is seeing intense rivalry because of the economy’s growing globalisation and technological improvements. It results in the fact that the supply chain’s complexity has grown in recent years, and supply chain systems are now more disruptive than ever because of the growing business environment’s uncertainties [3].
The firms should be able to handle the disruption In all three stages, and strategies should be formulated beforehand. Despite disruptions, firms learn from each event and generate new knowledge and experience, and this learning remains an implicit component of supply chain resilience. Supply chain practises demand the incorporation of sustainability metrics, as sustainability encourages organisations to perform things in a responsive manner. Disruptions provide an opportunity for constant learning within organisations so they can understand, learn, and implement from the actions, previous interventions, and experiences. Thus, complexity creates greater uncertainty throughout the supply chain, providing firms with additional opportunities for learning [4].

2. Impact of Supply Chain Complexity on Knowledge Transfer

In previous studies on complex supply chain networks [5][6][7], researchers and industry professionals have examined the supply chain networks with regards to the associated complexities. Nevertheless, the growing focus on supply chain complexity reflects the growing developments in the field of supply chain management. More researchers are looking at systems and networks rather than just dyadic partnerships to better reflect on the complex structure of global supply chain networks [8][9].

According to Sabahi and Parast, supply chains are systems made up of several entities and processes with various risk perceptions and vulnerabilities [10]. The problem of supply chain complexity has received widespread recognition in both academic research and practice. The complexity of the supply chain raises several ambiguities, difficulties, and sensitive issues for supply chain management [11]. Iftikhar et al. highlight that supply chains are becoming more disruptive, and if the complexity is not successfully handled, it might have negative effects on organisations [12]. Supply chain collaborations and internal activities contribute both externally and internally to the complexity of supply chain networks [13]. Marriotti argues that managerial decisions are also compromised due to the intricacies of supply chain systems, a challenge further exacerbated by the elevated complexity of goods, processes, and collaborations [14]. While complex linkages and interactions between entities are presented by global supply chains, higher operating expenses, lower customer satisfaction, delayed deliveries, a lack of knowledge transfer, and integration among supply chain partners are some of the essential negative effects of supply chain complexity [15]. A rising proportion of customers in industrialised regions view sustainability initiatives as more of an obligation than an added value, and this trend is particularly prevalent where growing populations are placing greater strain on the environment.

Figure 1 is a conceptual model by Wilding that illustrates a framework for explaining the uncertainties within a supply chain. Wilding argues that the three elements of Amplification, Deterministic Chaos, and Parallel Interactions, when combined, may dramatically raise the supply chain’s level of complexity and unpredictability [16].
Figure 1. Supply chain complexity triangle and dimensions of supply chain complexity (adapted from [16][17]).
Knowledge transfer is one of the most promising ways to increase firms’ competitiveness. It is a complex process that necessitates firms handling several tasks, such as creating routines that promote communication and collaboration. Along with collaborative networks, it facilitates sharing ideas and solutions with partners. According to Christopher and Lee, knowledge transfer in supply chain networks contributes to risk reduction, and it should be a top priority for firms [18]. Large businesses practise knowledge transfer internally and externally to promote supply chain resilience [19]. Knowledge transfer and adequate experience enhance the system’s capacity to handle any disruption. It can be further broken down into three main phases: before, during, and after a disruption [20]
The adoption of new technologies and their capacities in knowledge production, according to Papa et al., have an impact on the constantly evolving nature of knowledge creation, generation, and dissemination in companies [21]. To achieve this, they make use of their current resources by transforming large amounts of data into fresh, insightful, and useful knowledge utilising predictive and prescriptive business analytics. These skills enable businesses to excel at managing forecasts, production, and quality control while also giving customers access to new data for better decision-making to achieve a competitive edge [22]. By enhancing communication between suppliers and customers, new information may be produced [23].

2.1. Contingency Theory

To achieve higher performance, contingency theory considers the contextual factors in the business’s decision-making environment. The basic concept of contingency theory is that businesses need to be adaptable and should be able to understand their operating environment [24]. This is especially important when examining supply chain complexity since both structural and dynamic factors can have an advantageous or disadvantageous impact on a variety of company outcomes [25], and numerous environmental elements, including geographic location, national culture, institutional circumstances, as well as dynamic environmental features such as excessive complexity or uncertainty, have an impact on these results [26].

2.2. Complex Adaptive System

An interconnected network of numerous firms that demonstrates adaptive behavior in response to both the environment and the system of entities itself is referred to as a complex adaptive system [27][28]. A complex adaptive system is a self-organising system that continuously evolves over time by reconfiguring its internal and external links [29]. According to Kim et al., a complex adaptive system is a suitable theory for understanding the topologies of supply chain networks [30].

2.3. Natural Accident Theory

Although it has not been commonly used in supply chain disruption literature, natural accident theory can contribute to supply network interruptions [31]. Systemic risk and natural accident theory are complementary approaches that help us comprehend disruption prorogation. Natural accident theory is based on complex and strongly connected systems. Accidents are unavoidable or even common in this system, and catastrophic failures are just regular flaws that go out of control [32]. Links to supply chain disruptions should be taken into consideration in order to avoid accidents. The interaction complexity of the system can create problems in supply chain networks [33].

2.4. Systems Theory

The field of information systems discusses the application of general systems theory [34]. The goal of systems theory is to analyse dynamic relationships between components and relationships between the organisation and the environment [35]. To predict the system’s response to changes and hindrances, it is crucial to assess its functionality and flexibility [36]. According to the first principle, a system’s ability to adapt to changing circumstances decreases as it becomes more complex. The second principle is that more resources are required to sustain a larger system. The third principle illustrates how smaller systems frequently interact with bigger ones and are components of them. The fourth principle, which has obvious implications for the second principle, is about the creation of systems. The structural and dynamic aspects of complexity are two that are well-established in the supply chain literature [37]. The presence of various elements or sub-elements in the system gives rise to structural complexity, also known as static complexity or dynamic complexity. One factor that affects structural (static) complexity is the number of suppliers, customers, and products in a system, as well as their geographic distribution.
Supply chain complexity refers to the extent to which an organisation’s supply chain consists of many different elements that interact in unpredictable ways [38]. Supply chain organisations may address a variety of consumer expectations by employing blockchain technology, quickly recalling products from the market when disrupted, and automating business processes with integrated responses to product quality by tracking product chains. Downstream complexity, which is generally linked to customer numbers and product categories, is typically referred to as customer base complexity. When the core enterprise’s goals meet shifting consumer requirements and expectations, a large customer base and a wide range of completed items with a shorter life cycle add to the complexity of the customer base [39]. Customers with a significant divergence in their demands can negatively impact an enterprise’s ability to operate efficiently when the complexity of the client base is great [40]. As customer diversity continues to grow, transaction costs also rise, decreasing the effectiveness of businesses in managing their clientele. At times, businesses see an increase in inventory costs and cash withdrawal periods as consumers become more geographically separated [41].
Additionally, a diversified customer base can be useful for assessing the effects of demand swings in downstream supply chains, which can be determined by the profitability of the company. Figure 2 outlines the role of knowledge transfer and technological advancements in supply chain systems. Figure 2 also highlights the significance of management structures, as when they expand, knowledge transfer and technological advancements increase; however, with the increasing size and structure of an organisation, uncertainty and complexity also increase. This denotes that complexities can arise as knowledge transfer and technological advancements increase. Therefore, it is essential to handle the uncertainties and complexities associated with it. Furthermore, Figure 2 also elaborates on the factors of uncertainty and complexity, which are delayed delivery times, delays in product delivery, and the impact on scheduling times eventually being late or changed. The management and structure are to be taken into consideration when exchanging knowledge and incorporating technology, as it is crucial to understand the factors affecting the organisation. For instance, some of these factors include the size of the organisation, the size of the client base, the location of suppliers, etc.
Figure 2. Role of Knowledge Transfer and technological advancements on Supply chain complexity (Adapted from [42]).
Xiao and Qi further elaborate that information exchange and effective communication across various levels and channels are crucial measures to prevent supply chain disruptions [43]. Since the ideal design for one product could not work for another, product variety is also a significant indicator of consumer base diversity. Consequently, when there is a large range of products, supply chain coordination has to be more effective [44]. While product complexity may not directly affect customer integration, businesses that produce complex products often employ both internal and supplier integration. Product variety has been shown to be positively correlated with supply chain integration parameters [45]. Yin and Ran emphasise the product life cycle as it is another important component that contributes to supply chain complexity; a shorter product life cycle results in quicker supply chain design modifications to accommodate varying degrees of demand uncertainty at various phases, as well as faster manufacturing and shorter lead times [46].
Even though supply chain complexity is unavoidable, successful businesses strive to comprehend it, reduce it to a minimum, and maintain efficient operations in supply chain networks.

References

  1. Weber, Y.; Tarba, S.Y. Strategic agility: A state of the art introduction to the special section on strategic agility. Calif. Manag. Rev. 2014, 56, 5–12.
  2. Del Giudice, M.; Maggioni, V. Managerial practices and operative directions of knowledge management within inter-firm networks: A global view. J. Knowl. Manag. 2014, 18, 841–846.
  3. Lee, M.C. Knowledge management and innovation management: Best practices in knowledge sharing and knowledge value chain. Int. J. Innov. Learn. 2016, 19, 206–226.
  4. Hussain, G.; Nazir, M.S.; Rashid, M.A.; Sattar, M.A. From supply chain resilience to supply chain disruption orientation: The moderating role of supply chain complexity. J. Enterp. Inf. Manag. 2023, 36, 70–90.
  5. Hobday, M. Product complexity, innovation and industrial organisation. Res. Policy 1998, 26, 689–710.
  6. Closs, D.J.; Jacobs, M.A.; Swink, M.; Webb, G.S. Toward a theory of competencies for the management of product complexity: Six case studies. J. Oper. Manag. 2008, 26, 590–610.
  7. Closs, D.J.; Nyaga, G.N.; Voss, M.D. The differential impact of product complexity, inventory level, and configuration capacity on unit and order fill rate performance. J. Oper. Manag. 2010, 28, 47–57.
  8. Choi, T.Y.; Wu, Z. Triads in supply networks: Theorizing buyer–supplier–supplier relationships. J. Supply Chain Manag. 2009, 45, 8–25.
  9. Hearnshaw, E.J.; Wilson, M.M. A complex network approach to supply chain network theory. Int. J. Oper. Prod. Manag. 2013, 33, 442–469.
  10. Sabahi, S.; Parast, M.M. Firm innovation and supply chain resilience: A dynamic capability perspective. Int. J. Logist. Res. Appl. 2020, 23, 254–269.
  11. Jermsittiparsert, K.; Srisawat, S. Complexities in a flexible supply chain and the role of knowledge transfer. Humanit. Soc. Sci. Rev. 2019, 7, 531–538.
  12. Iftikhar, A.; Purvis, L.; Giannoccaro, I.; Wang, Y. The impact of supply chain complexities on supply chain resilience: The mediating effect of big data analytics. Prod. Plan. Control. 2022, 34, 1562–1582.
  13. Chand, P.; Kumar, A.; Thakkar, J.; Ghosh, K.K. Direct and mediation effect of supply chain complexity drivers on supply chain performance: An empirical evidence of organizational complexity theory. Int. J. Oper. Prod. Manag. 2022, 42, 797–825.
  14. Mariotti, J.L. The Complexity Crisis: Why too Many Products, Markets, and Customers are Crippling Your Company—And What to Do about It; Simon and Schuster: New York, NY, USA, 2007.
  15. Lee, G. Supply Chain Complexity and Supply Chain Resilience: A Literature Review; EasyChair Preprint: Atlanta, GA, USA, 2023.
  16. Wilding, R. The supply chain complexity triangle: Uncertainty generation in the supply chain. Int. J. Phys. Distrib. Logist. Manag. 1998, 28, 599–616.
  17. Milgate, M. Supply chain complexity and delivery performance: An international exploratory study. Supply Chain Manag. Int. J. 2001, 6, 106–118.
  18. Christopher, M.; Lee, H. Mitigating supply chain risk through improved confidence. Int. J. Phys. Distrib. Logist. Manag. 2004, 34, 388–396.
  19. Soni, U.; Jain, V.; Kumar, S. Measuring supply chain resilience using a deterministic modeling approach. Comput. Ind. Eng. 2014, 74, 11–25.
  20. Soni, U.; Jain, V. Minimizing the vulnerabilities of supply chain: A new framework for enhancing the resilience. In Proceedings of the 2011 IEEE International Conference on Industrial Engineering and Engineering Management, Singapore, 6–9 December 2011; IEEE: Piscataway, NJ, USA, 2011; pp. 933–939.
  21. Papa, A.; Chierici, R.; Ballestra, L.V.; Meissner, D.; Orhan, M.A. Harvesting reflective knowledge exchange for inbound open innovation in complex collaborative networks: An empirical verification in Europe. J. Knowl. Manag. 2021, 25, 669–692.
  22. Philip, J. An application of the dynamic knowledge creation model in big data. Technol. Soc. 2018, 54, 120–127.
  23. Paulin, D.; Suneson, K. Knowledge transfer, knowledge sharing and knowledge barriers–three blurry terms in KM. Lead. Issues Knowl. Manag. 2015, 2, 73.
  24. Ketokivi, M. Elaborating the contingency theory of organizations: The case of manufacturing flexibility strategies. Prod. Oper. Manag. 2006, 15, 215–228.
  25. Brandon-Jones, E.; Squire, B.; Van Rossenberg, Y.G. The impact of supply base complexity on disruptions and performance: The moderating effects of slack and visibility. Int. J. Prod. Res. 2015, 53, 6903–6918.
  26. Brandon-Jones, A.; Knoppen, D. The role of strategic purchasing in dynamic capability development and deployment: A contingency perspective. Int. J. Oper. Prod. Manag. 2018, 38, 446–473.
  27. Day, J.M. Fostering emergent resilience: The complex adaptive supply network of disaster relief. Int. J. Prod. Res. 2014, 52, 1970–1988.
  28. Pathak, S.D.; Day, J.M.; Nair, A.; Sawaya, W.J.; Kristal, M.M. Complexity and adaptivity in supply networks: Building supply network theory using a complex adaptive systems perspective. Decis. Sci. 2007, 38, 547–580.
  29. Anderson, P. Perspective: Complexity theory and organization science. Organ. Sci. 1999, 10, 216–232.
  30. Kim, Y.; Chen, Y.S.; Linderman, K. Supply network disruption and resilience: A network structural perspective. J. Oper. Manag. 2015, 33, 43–59.
  31. Speier, C.; Whipple, J.M.; Closs, D.J.; Voss, M.D. Global supply chain design considerations: Mitigating product safety and security risks. J. Oper. Manag. 2011, 29, 721–736.
  32. Perrow, C. The limits of safety: The enhancement of a theory of accidents. J. Contingencies Crisis Manag. 1994, 2, 212–220.
  33. Marley, K.A.; Ward, P.T.; Hill, J.A. Mitigating supply chain disruptions–a normal accident perspective. Supply Chain Manag. Int. J. 2014, 19, 142–152.
  34. Janvier-James, A.M. A new introduction to supply chains and supply chain management: Definitions and theories perspective. Int. Bus. Res. 2012, 5, 194–207.
  35. Lai, C.H.; Huili Lin, S. Systems theory. In the International Encyclopedia of Organizational Communication; John Wiley & Sons: Hoboken, NJ, USA, 2017; pp. 1–18.
  36. Farsi, M.; Hosseinian-Far, A.; Daneshkhah, A.; Sedighi, T. Mathematical and computational modelling frameworks for integrated sustainability assessment (ISA). In Engineering for Cloud Computing and Big Data Analytics; Springer: Cham, Switzerland, 2017; pp. 3–27.
  37. Serdarasan, S. A review of supply chain complexity drivers. Comput. Ind. Eng. 2013, 66, 533–540.
  38. Dittfeld, H.; Scholten, K.; Van Donk, D. Burden or blessing in disguise: Interactions in supply chain complexity. Int. J. Oper. Prod. Manag. 2018, 38, 314–332.
  39. Chen, M.; Liu, H.; Wei, S.; Gu, J. Top managers’ managerial ties, supply chain integration, and firm performance in China: A social capital perspective. Ind. Mark. Manag. 2018, 74, 205–214.
  40. de Leeuw, S.; Grotenhuis, R.; van Goor, A.R. Assessing complexity of supply chains: Evidence from wholesalers. Int. J. Oper. Prod. Manag. 2013, 33, 960–980.
  41. Lorentz, H.; Töyli, J.; Solakivi, T.; Hälinen, H.M.; Ojala, L. Effects of geographic dispersion on intra-firm supply chain performance. Supply Chain Manag. Int. J. 2012, 17, 611–626.
  42. Vachon, S.; Klassen, R.D. An exploratory investigation of the effects of supply chain complexity on delivery performance. IEEE Trans. Eng. Manag. 2002, 49, 218–230.
  43. Xiao, T.; Qi, X. Price competition, cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailers. Omega 2008, 36, 741–753.
  44. Kanda, A.; Deshmukh, S.G. Supply chain coordination: Perspectives, empirical studies and research directions. Int. J. Prod. Econ. 2008, 115, 316–335.
  45. Shou, Y.; Kang, M.; Park, Y.W. Product complexity, variety and supply chain integration. In Supply Chain Integration for Sustainable Advantages; Springer: Singapore, 2022; pp. 31–48.
  46. Yin, W.; Ran, W. Utilizing blockchain technology to manage the dark and bright sides of supply network complexity to enhance supply chain sustainability. Complexity 2022, 2022, 7734580.
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