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Adaptive supply chains in industrial districts: A complexity science approach focused on learning

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  • Giannoccaro, Ilaria

Abstract

This paper investigates the relationship between learning and adaptation in supply chains located within industrial districts, with the aim of identifying the best adaptive supply chain. It is motivated by the increasing attention that the design of adaptive supply chains has been receiving in recent years, as it is considered one of the most important critical factors in gaining sustainable competitive advantage in the current hypercompetitive environment. Focusing on two learning processes (i.e., by imitation and by interacting), diverse types of adaptive supply chains recognizable within industrial districts are compared by means of an agent-based simulation on the basis of their adaptive performance in environments characterized by different level of complexity and turbulence. The results confirm that the supply chain type influences the relationship between learning and adaptation and that both the product complexity and the turbulence of the environment moderate this effect. Finally, the best adaptive supply chain in each type of context is identified.

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  • Giannoccaro, Ilaria, 2015. "Adaptive supply chains in industrial districts: A complexity science approach focused on learning," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 576-589.
    • Handle: RePEc:eee:proeco:v:170:y:2015:i:pb:p:576-589
    DOI: 10.1016/j.ijpe.2015.01.004
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    Cited by:

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    2. Massari, Giovanni F. & Giannoccaro, Ilaria & Carbone, Giuseppe, 2019. "Are distrust relationships beneficial for group performance? The influence of the scope of distrust on the emergence of collective intelligence," International Journal of Production Economics, Elsevier, vol. 208(C), pages 343-355.
    3. Massari, Giovanni Francesco & Giannoccaro, Ilaria, 2021. "Investigating the effect of horizontal coopetition on supply chain resilience in complex and turbulent environments," International Journal of Production Economics, Elsevier, vol. 237(C).
    4. Luca Fraccascia & Ilaria Giannoccaro & Vito Albino, 2017. "Efficacy of Landfill Tax and Subsidy Policies for the Emergence of Industrial Symbiosis Networks: An Agent-Based Simulation Study," Sustainability, MDPI, vol. 9(4), pages 1-18, March.
    5. Ojha, Divesh & Shockley, Jeff & Acharya, Chandan, 2016. "Supply chain organizational infrastructure for promoting entrepreneurial emphasis and innovativeness: The role of trust and learning," International Journal of Production Economics, Elsevier, vol. 179(C), pages 212-227.
    6. Bressanelli, Gianmarco & Visintin, Filippo & Saccani, Nicola, 2022. "Circular Economy and the evolution of industrial districts: a supply chain perspective," International Journal of Production Economics, Elsevier, vol. 243(C).
    7. Giannoccaro, Ilaria & Carbone, Giuseppe, 2017. "An Ising-based dynamic model to study the effect of social interactions on firm absorptive capacity," International Journal of Production Economics, Elsevier, vol. 194(C), pages 214-227.
    8. Giannoccaro, Ilaria & Galesic, Mirta & Massari, Giovanni Francesco & Barkoczi, Daniel & Carbone, Giuseppe, 2020. "Search behavior of individuals working in teams: A behavioral study on complex landscapes," Journal of Business Research, Elsevier, vol. 118(C), pages 507-516.
    9. Reza Yazdanparast & Reza Tavakkoli-Moghaddam & Razieh Heidari & Leyla Aliabadi, 2021. "A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 611-631, June.
    10. Fraccascia, Luca, 2020. "Quantifying the direct network effect for online platforms supporting industrial symbiosis: an agent-based simulation study," Ecological Economics, Elsevier, vol. 170(C).
    11. Ojha, Divesh & Acharya, Chandan & Cooper, Danielle, 2018. "Transformational leadership and supply chain ambidexterity: Mediating role of supply chain organizational learning and moderating role of uncertainty," International Journal of Production Economics, Elsevier, vol. 197(C), pages 215-231.

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