Multi-tier Supply Chain Resilience: Integrating Risk Management Strategies

Kirjoittaja Seray Mirasci palkittiin huhtikuussa 2025 LOGYn kannusteapurahalla LUT-yliopistossa tekemästään väitöskirjatyöstä. Hänen väitöskirjansa nimi on “Multi-tier Supply Chain Resilience: Integrating Risk Management Strategies”.

The supply chain management (SCM) process involves a series of unexpected force-majeure situations requiring rapid, accurate decisions (DuHadway et al., 2019; Finkenstadt and Handfield, 2021). Supply chain risk can be defined as “the potential occurrence of an incident associated with inbound supply from individual supplier failures or the supply market in which its outcomes result in the inability of the purchasing firm to meet customer demand or cause threats to customer life and safety.” (Zsidisin, 2003). Supply chain risk should not be understood as an unwanted element of the supply chain; rather, it should be recognized as a process that needs to be correctly categorized, understood, and constructed, involving the development and planning to strengthen the existing supply chain (Kähkönen and Patrucco, 2022; Yang et al., 2024).

To study the supply chain risks, we selected Türkiye as a representative of a developing country. The February 2023 earthquakes in Türkiye and northern Syria were classified as the deadliest earthquakes in Türkiye's history by geology and medical researchers (Görmeli Kurt et al., 2023; Kusky et al., 2023; Tayfur et al., 2024; Uwishema, 2023) with measuring 7.7 and 7.6 on the Richter scale (Cinar et al., 2023; Dündar, 2023). These twin earthquakes had significant negative impacts across various industries (Onat et al., 2022).

These earthquakes serve as a stark reminder of how natural disasters can severely disrupt global supply chains, highlighting the urgent need for businesses to build resilience and adaptability. My doctoral research aims to address this very challenge by exploring how supply chain dynamics in disaster contexts and identifying supply chain risks and necessary capabilities that companies can adopt to better prepare for and respond to such events. The thesis is structured into three interconnected studies, each offering both theoretical contributions and practical guidance for managing supply chain risks and complexities in times of crisis.

The first study investigates the supply chain risk categorization (such as direct supply chain risks and indirect supply chain risks) that the 2023 Türkiye earthquakes posed to supply chains. Through in-depth, semi-structured interviews with 23 companies spanning the textile, food, and automotive sectors, the research uncovers how earthquakes disrupt supply networks at multiple levels. The findings categorize risks into clear groups, providing a structured approach that practitioners can use to mitigate disaster-induced disruptions.

Building on these findings, the second study delves deeper into dynamic capabilities that supply chains need in context of the earthquakes. Using empirical data from the same set of firms, this research identifies dynamic capabilities that help supply chains (such as sensing, seizing and reconfigurating) effectively during crises. The second study offers practical recommendations for supply chain managers and policymakers alike, aiming to enhance responsiveness in high-risk environments.

The third study takes a broader view by analyzing risk management practices across multiple industries. By compiling 10-K reports from 600 companies in the manufacturing sector, this research applies advanced topic modeling techniques to develop comprehensive risk dictionaries. These tools will help businesses better understand the risks embedded within the supply chains. Currently in the dictionary development phase, this research promises to deliver valuable frameworks for assessing supply network complexity and improving overall risk management.

Alongside my supply chain risk management studies, digitalization is undeniably critical for supply chains, so my work also includes two extra JUFO2-level publications focused on Artificial Intelligence (AI) applications. These papers explore the role of AI in improving supply chain decision-making, from developing steel price forecasting algorithms for purchasing departments to using AI applications for reducing CO2 emissions in the food sector. For those interested in exploring AI further about price forecastings and reducing CO2 emissions, publications are available as follows:

• Mirasçı, S., & Aksoy, A. 2025. Data-Driven purchasing strategies: Price prediction models and strategy development. Expert Systems with Applications, 266: 125986.
• Mirasçı, S., Uygur, S., & Aksoy, A. 2025. Advancing energy efficiency: Machine learning based forecasting models for integrated power systems in food processing company. International Journal of Electrical Power & Energy Systems, 165: 110445.

With this thesis, I aim to bridge the gap between academia and practice, offering insights that help businesses navigate the complexities of disaster-prone environments and strengthen their supply chains to be more resilient and digital driven for the future.

Seray Mirasci
LUT Business School