Risk management has become an essential component of modern business strategy, particularly in the context of increasingly complex and interconnected supply chains. While existing literature extensively discusses the categorization of risks, the key phases of risk management, and the strategies available to mitigate risks, there remains a gap in understanding how companies decide which strategy to adopt in different scenarios. This thesis begins with a comprehensive literature review, analyzing various risk classifications, the structured phases of the risk management process, and the strategic approaches proposed by researchers. Building on this theoretical foundation, the study extends its scope to real-world case studies, identifying the key factors that influence companies’ decision-making when selecting a risk management strategy—an aspect previously underexplored in the literature. These factors include geographical location, regulatory environment, technological capabilities, financial constraints, corporate risk tolerance, and supply chain interdependencies. Furthermore, this research investigates the potential risks and corresponding mitigation strategies at different stages of supply chain planning, providing a structured framework for businesses to proactively manage vulnerabilities. Beyond risk prevention, the study also explores how the implementation of risk management strategies transforms a company’s supply chain, affecting operational efficiency, supplier relationships, inventory management, and overall resilience. Finally, this thesis examines the role of emerging technologies in reshaping risk management practices. It highlights how innovations such as Artificial Intelligence (AI), Machine Learning, Digital Twins, and Blockchain can be leveraged to enhance risk identification, predictive modeling, and decision-making processes. As businesses strive to navigate an increasingly uncertain global landscape, the integration of these technologies represents a significant opportunity to shift from reactive to proactive risk management, ensuring long-term competitiveness and stability. By combining theoretical insights with empirical analysis, this research provides a holistic perspective on risk management, bridging gaps in the existing literature and offering practical recommendations for organizations aiming to develop more structured, data-driven, and technologically advanced risk management strategies.
La gestione del rischio è diventata una componente essenziale della moderna strategia aziendale, in particolare nel contesto di catene di fornitura sempre più complesse e interconnesse. Sebbene la letteratura esistente discuta ampiamente la categorizzazione dei rischi, le fasi chiave della gestione del rischio e le strategie disponibili per mitigare i rischi, rimane una lacuna nella comprensione di come le aziende decidono quale strategia adottare nei diversi scenari. Questa tesi inizia con una revisione completa della letteratura, analizzando varie classificazioni del rischio, le fasi strutturate del processo di gestione del rischio e gli approcci strategici proposti dai ricercatori. Basandosi su queste basi teoriche, lo studio estende il suo ambito a casi di studio del mondo reale, identificando i fattori chiave che influenzano il processo decisionale delle aziende nella scelta di una strategia di gestione del rischio, un aspetto precedentemente sottoesplorato in letteratura. Questi fattori includono la posizione geografica, il contesto normativo, le capacità tecnologiche, i vincoli finanziari, la tolleranza al rischio aziendale e le interdipendenze della catena di fornitura. Inoltre, questa ricerca indaga i potenziali rischi e le corrispondenti strategie di mitigazione nelle diverse fasi della pianificazione della catena di approvvigionamento, fornendo un quadro strutturato affinché le aziende possano gestire in modo proattivo le vulnerabilità. Oltre alla prevenzione del rischio, lo studio esplora anche il modo in cui l’implementazione delle strategie di gestione del rischio trasforma la catena di fornitura di un’azienda, influenzando l’efficienza operativa, le relazioni con i fornitori, la gestione delle scorte e la resilienza complessiva. Infine, questa tesi esamina il ruolo delle tecnologie emergenti nel rimodellare le pratiche di gestione del rischio. Evidenzia come innovazioni come l’intelligenza artificiale (AI), il machine learning, i digital twin e la blockchain possono essere sfruttate per migliorare l’identificazione del rischio, la modellazione predittiva e i processi decisionali. Mentre le aziende si sforzano di navigare in un panorama globale sempre più incerto, l’integrazione di queste tecnologie rappresenta un’opportunità significativa per passare da una gestione del rischio reattiva a quella proattiva, garantendo competitività e stabilità a lungo termine. Combinando approfondimenti teorici con analisi empiriche, questa ricerca fornisce una prospettiva olistica sulla gestione del rischio, colmando le lacune nella letteratura esistente e offrendo raccomandazioni pratiche per le organizzazioni che mirano a sviluppare strategie di gestione del rischio più strutturate, basate sui dati e tecnologicamente avanzate.
Supply chain risk management: a literature review, case studies and the role of technological innovation
MELI, MATTIA
2023/2024
Abstract
Risk management has become an essential component of modern business strategy, particularly in the context of increasingly complex and interconnected supply chains. While existing literature extensively discusses the categorization of risks, the key phases of risk management, and the strategies available to mitigate risks, there remains a gap in understanding how companies decide which strategy to adopt in different scenarios. This thesis begins with a comprehensive literature review, analyzing various risk classifications, the structured phases of the risk management process, and the strategic approaches proposed by researchers. Building on this theoretical foundation, the study extends its scope to real-world case studies, identifying the key factors that influence companies’ decision-making when selecting a risk management strategy—an aspect previously underexplored in the literature. These factors include geographical location, regulatory environment, technological capabilities, financial constraints, corporate risk tolerance, and supply chain interdependencies. Furthermore, this research investigates the potential risks and corresponding mitigation strategies at different stages of supply chain planning, providing a structured framework for businesses to proactively manage vulnerabilities. Beyond risk prevention, the study also explores how the implementation of risk management strategies transforms a company’s supply chain, affecting operational efficiency, supplier relationships, inventory management, and overall resilience. Finally, this thesis examines the role of emerging technologies in reshaping risk management practices. It highlights how innovations such as Artificial Intelligence (AI), Machine Learning, Digital Twins, and Blockchain can be leveraged to enhance risk identification, predictive modeling, and decision-making processes. As businesses strive to navigate an increasingly uncertain global landscape, the integration of these technologies represents a significant opportunity to shift from reactive to proactive risk management, ensuring long-term competitiveness and stability. By combining theoretical insights with empirical analysis, this research provides a holistic perspective on risk management, bridging gaps in the existing literature and offering practical recommendations for organizations aiming to develop more structured, data-driven, and technologically advanced risk management strategies.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/235634